CONCRETE Count Noun Superset      [mnemonic:  CO]  [3]

Definition: CONCRETE Count Nouns are countable physical things, either man-made or natural, including parts of the human body.  CONCRETE Count Nouns contain both sets and subsets as shown in the frame above.

CONCRETE Nouns are always count nouns and, unless in the plural, generally cannot occur without a preceding article or quantifier. For example:   Computers are effective.  *Computer is effective (illegal).  Note that the distinction between count nouns and MASS Nouns is critical to parsing in languages such as English.

Principal sets of CONCRETE nouns are

Other sets are

Functional things tend to be passive, i.e. typically do not act of their own accord and generally require an agent to use them.  Hence they are more instrumental in nature.  Agents typically do work in and of themselves.  

This distinction may sometimes seem arbitrary.  For example, hinge is a fastener under functional things and clearly does work of itself but is not coded as an agent. Airplane, on the other hand, obviously does require an agent and yet is  coded under agentives as a vehicle.  As a rule, agentives have a source of power or energy in themselves; functionals do not.

Note that parts of the human/animal body are also classified as CONCRETE.  Things like heart, brain, digestive tract, stomach, and organs in general are machines/systems under agentives.  Words like teeth, fingernail, toes, lips, tendons, ligaments, bones, etc. belong to various subsets under functionals.

Tips:  If a word belongs in the CONCRETE Superset but none of the sets or subsets seem to apply, use the undifferentiated set.

Caution!   If the noun can be used in the singular without an article or quantifier, e.g. gas, it should be coded under the MASS Superset. 

functionals    [mnemonic: COfunc]   [code: 3 34]

Definition: Functionals tend to be passive, non-agentive, i.e. typically do not act of their own accord and generally require an agent to use them.  Hence they are more instrumental in nature.  By contrast, agentives typically do work in and of themselves. 

Functionals comprise the following subsets:

Tips:  The distinction between functionals and agentives may sometimes seem arbitrary.  For example, hinge is a device under functionals and clearly does work of itself but should not be coded as an agent. Airplane, on the other hand, obviously requires an agent to operate and yet should be coded under agentives as a vehicle.  As a rule, agentives have a source of power or energy in themselves; functionals do not.

devices/tools   [mnemonic: COtool]  [code: 3 34 720]

Definition:    Devices, tools, or instruments that do not qualify as agentives.  The devices/tools subset can include anatomical parts.  In general, one can ask of devices/tools such questions as "what is it used for?"  .

Examples:    armature, button, claw, diode, divider, drill bit, eraser, hammer, handle, hinge, hubcap, microscope, molar, muffler, muscle, pencil, plunger, razor blade, ruler, stapler, steering wheel, thimble, valve  

Tips:   When preceded by the preposition with, this preposition usually has the sense of by means of.  E.g., He installed the cabinet with a screwdriver versus He installed the cabinet with a glass door.

Caution:   Powered devices, tools, instruments should be coded agentives.

 fasteners  [mnemonic: COfast]  [code: 3 34 721]

Definition:    Any physical thing which makes fast, joins, or attaches.

Examples:    bolt, brad. buckle, cinch, clasp, coupling, dowel, hinge, hitch, latch, ligament, lock, lug, nail, nut, paper clip, prong, rivet, screw, skewer, snap, staple, tack, talon, tendon, tenon, yoke

Caution:   Words like scotch tape, masking tape, duct tape, Velcro, adhesive are not count nouns and should be coded under functional mass under the MASS Superset.

bearing surfaces   [mnemonic: COsurf]  [code: 3 34 722]

Definition:   Any thing that functions as a support surface.

Examples:   bed, bench, counter, cot, couch, dais, divan, deck, desk, floor, highchair, ladder, ledge, mantel, mattress, ottoman,  pallet, platform, rack, sawhorse, scaffold, shelf, sill, stool, table, tray

Tips:   When used with the preposition from, this preposition has the sense off of.  E.g., She took the material from the table.

Caution:   Some things which might appear to be bearing surfaces fall into other categories. For example, stage should be coded functional place under PLACE Superset.  Stairs should be coded under paths in PLACE Superset. 

Exceptionally, the word saddle should be coded as a receptacle under functionals because when used with the preposition from, that preposition takes the meaning out of rather than off of.  

When used with the preposition from, some words, like bed, may cause that preposition to take on different meanings; e.g., He got up from his bed can mean either He got out of or He got off of.   The Logos system codes bed as a bearing surface as its most probable code.  E,g., He took the pillow off the bed where off has the sense off of.  

receptacles     [mnemonic: COrecp]     [code: 3 34 659]

Definition:    Containers in which something is stored, held or carried.

Examples:    barrel, bin, bottle, box, cabinet, carton, container, cubby hole, drum, gear housing, package, pan, pot, safe, thermos, tub, vacuum chamber, vessel

Tips:   When used with the preposition from, this preposition has the sense of out of.   E.g., He took the material from the box.

Caution:   Words such as barn, grave, pit, closet, foyer, lobby, vault should not be coded as receptacles, but as enclosed space under the PLACE Superset.  The distinction is designed to reflect the human scale and geographical connotation of PLACE nouns.

Words such as cavity, enclosure should not be coded as receptacles under CONCRETE nouns but as receptacles under ASPECTIVES.  Such words are "aspective" because they do not constitute concrete things in themselves (as in the case of enclosure) or because they are aspects of something else (as in the case of cavity).

conduits    [mnemonic:  COcond]    [code: 3 34 745]

Definition:    Any concrete thing that serves as a channel through which fluids or energy forces may flow.

Examples:    airshaft, artery, bowel, capillary, catheter, duct, faucet, gaspipe, hose, nerve, nose, nozzle, pipe, pipeline, rectum, siphon, sleeve, spout, tube, vein, windpipe

Tips:   When used with the preposition through, this preposition has the sense of along.   E.g., Blood flows through veins.

When used with the preposition from, this preposition has the sense of out of.  E.g., Water drips from the faucet.

Caution:   Some conduit-type words fall into other categories.  E.g., A word like intestines should be coded as agentive.  Tubing should be coded under MASS Superset.

Words such as tunnel, trench, ravine, riverbed, canal and passage should  be coded  under the PLACE Superset.  The distinction is designed to reflect the human scale and geographical connotation of PLACE nouns.

links/bridges    [mnemonic: COlink]    [3 34 526]

Definition:    Any thing functioning as a span or passageway (non-human scale), including parts of the body

Examples:    circuit, ligament, ligature, overpass, ramp, span, tendon, viaduct

Tips:    When used with the preposition over, this preposition has a sense akin to across.   E.g., He walked over the bridge.   The signal came over the circuit.

Caution:   Words like chain, network belong in the ASPECTIVE Superset.   A word like circuitry is a MASS Noun 

thresholds/focal points/barriers  

[mnemonic: CObarr]    [3 34 525]

Definition:    This is a catch-all subset for things which serve as spatial limits, boundaries and barriers; or serve as focal points, or as thresholds.

Examples of Focal Points and Thresholds:    archway, door, entranceway,   faucet, gate, hatch, intake, port (hardware sense), screen door, seacock, seam, spigot, threshold, turnstile, window

Examples of Barriers and Boundaries:   backstop, baffle, bulkhead, ceiling, dike, fence, floodgate, folding screen, pale and paling (in the barrier sense),  partition, rail, railing, seawall, wall

Tips:   When used with the preposition through, this preposition has a sense akin to across.   E.g., Sounds came through the wall.   He came through the door. (Note how the sense of through here differs from through in conduits: Water flowed through (along) the pipe. 

Caution:   A number of words that look like they belong here should rather be coded as ASPECTIVES;  e.g.,  entrance, exit, opening, hole, hub, nucleus, center, horizon, gap, intersection, target, ceiling, edge, front, back, side, face. 

The ASPECTIVES code is more appropriate here because these words tend to be aspects of something else;  e.g., center of the city, exit of the building, etc.  (See ASPECTIVES for further explanation.)

A number of words that look like they belong here should rather be coded as PLACE;  e.g., dam, roadblock, border.  PLACE is more appropriate because of the human scale involved and their geographical connotation.

cloth things    [mnemonic: COcloth]    [3 34 785]

Definition:    Soft things made of fabric, leather, etc.

Examples:    afghan, banner, blanket, blouse, curtain, drape, dress, flag, hat, mitten, parka, pennant, rug, sail, scarf, shawl, sheet, shirt, shoe, slacks, slipper, sock, sweater, tie, towel

Caution:   Words like clothing, upholstery, carpet should be coded under the MASS Superset.  Words like sleeping bag and pillow case should be coded as receptacles; e.g., Take the pillow from (out of) the pillow case.  

Words like tent should be coded as enclosed space under PLACE to reflect the human scale.

structural elements    [mnemonic: COstruc]    [3 34 612]

Definition:    Things that function structurally, including parts of the body

Examples:   bar, beam, bone, capital, capstone, chassis, column, cornerstone,   frame, gaffe, girder, keystone, lattice, mast, pane, panel, pilaster, pillar,   pole,  post, roof, rafter, rod, shaft, skeleton, spar, strut

Tips:   When used with the preposition from, this preposition typically has the sense off of.  E.g., He fell from (off of) the roof. 

Note that roof is a structural element, whereas ceiling is a threshold/focal point/barrier.  (You can remove a roof, but you can't remove a ceiling.)

Caution:   Words like paneling, timber, glass are coded under the MASS Superset.  

concretization of verbals    [mnemonic: COverb]    [3 34 211]

Definition:    Concrete things derived from a verbal action. 

Examples:    carving(s), casting(s), coating(s), covering, knot, mounting, partitioning, projecting, refill, shaving(s), stitch, threading, weld, winding

Caution:   This is a narrow set of nouns and should not be confused with strong verbals under ABSTRACT or with functional mass nouns, such as piping, wiring, tubing, planking, etc.

concretization of mass nouns [mnemonic: COmass]    [3 34 210]

Definition:    A noun phrase the first word of which is a mass noun but which does not function as a mass noun because of the head word which is not mass. 

Examples:    acid lining, iron vein

Caution:   This is a very narrow set of nouns.

product/brand names    [mnemonic: CObrand]    [3 34 209]

Definition:    Things that are brand names or product names.  This is a very restricted set.  Note the "Cautions" below.

Examples:    Camry

Caution:   Only entries that are purely product or brand names should be given this code, i.e. do not use this code if the term is also a company name; e.g., Ford.   Doing otherwise can deprive the system of critical intelligence of the word's agentive characteristic.

Do not code brand names which are mass nouns here;  e.g., Kleenex, Sprite, Coke.  Such words should be coded under the MASS Noun Superset. 

Be sure to capitalize the entry to avoid possible confusion with common nouns (e.g. Coke versus coke).

undifferentiated functionals   

[mnemonic: COundfunc ]    [3 34 217]

Definition:    Nouns denoting functional concrete things which have not been covered by other categories within the functional set.  

Examples:    bauble, gem, jewel, necklace, papillote, pawn, ornament, souvenir, trinket

agentives    [mnemonic: COagen ]    [3 35]

Definition:    Agentives tend to be active, i.e. typically have a source of energy in themselves and do some kind of work of their own accord; hence, the agentive designation. They are contrasted with functionals which tend to be more passive in nature.   

Agentives comprise the following subsets:

Tips:   Agentives as distinct from functionals typically have two characteristics: (a) they do work in and of themselves;  (b) they have a source of energy in themselves.  Some functionals like hinge, valve, muffler, armature satisfy (a) but not (b).

Agents play an important role in parsing. 

If none of the subsets under agentives seem to apply, use the undifferentiated set.

Caution:   Agentives are always count nouns and, unless pluralized, generally cannot occur without a preceding article or quantifier. For example: *Computer is effective (illegal).  Computers are effective (legal).   If the word can occur in the singular without an article or quantifier, it should be coded under the MASS Superset.

software    [mnemonic: COsoft ]    [3 35 300]

Definition:    All types of computer programs and routines.  This includes both generic terms and specific product names.

Examples:    applet, browser, compiler, Coreldraw, form handler, FrontPage, interpreter, Linux, operating system, OS2, PageMaker, patch, Power Point, program, RDBMS, routine, software driver, software application, software editor, software filter, software function, Solaris, spelling checker, spider (Internet sense), subroutine, SunOS, Visio, Windows, wizard

Tips:   Include in this subset those software agents which function with some degree of autonomy;  a single line of program instruction would not satisfy this condition.

This category does include firmware.

Caution:   The words software and firmware and all compounds ending in these words have the properties of a mass noun and should be coded under functional mass.

Terms like line of code, program instruction, hyperlink, hot button, branch instruction, Do Loop should not be coded here as software under CONCRETE Superset, but as instructional data under INFORMATION Superset. 

Terms like web page, web site should be coded as recorded data under INFORMATION Superset.    

Terms like URL, ASCII, HTML, JAVA should be coded as symbolic data under INFORMATION Superset.

Product names are included here unless the product name is identical with the company name, in which case the word should be coded as proper organization names under the ANIMATE Superset.

concrete chemical agents   [mnemonic: COchem ]    [3 35 702]

Definition:    Chemical substances that cause change and do not qualify as MASS Nouns

Examples:    catalyst, charge, explosive, fireworks, payload, reagent, sedative, warhead

Tips:   Include non-chemical warheads and bombs in this subset. 

Caution:   Proper names of medicines and chemicals should be coded under chemical agent in the MASS Noun Superset when such names function as mass nouns; viz., can occur after some in the singular ( i.e., are not count nouns).   For example, some Prozac, some Bufferin, etc.

Product names which are count nouns are included here unless the product name is identical with the company name, in which case the word should be coded as proper organization names under the ANIMATE Superset.

Weapons like guided missiles should be coded as vehicles under agentives; smart bombs should be coded as machines/systems under agentives.

machines/systems   [mnemonic: COmach ]    [3 35 750]

Definition:    Hardware or organs that satisfy the conditions of an agent: (a) performs work in and of itself; (b) has its energy source in itself.

Examples:    air conditioner, battery, camera, carburetor, computer, drill,   electron microscope, engine, fan, firearm, furnace, generator, heart, laser, liver, microprocessor, monitor, multiplexer, pacemaker, pancreas, printer, radiator, reactor, recorder, refrigerator, scanner, stove, terminal, transformer, weapon

Tips:    See general explanation of agentives above.

Caution:   Product names are included here unless the product name is identical with the company name, in which case the word should be coded as proper organization names under the ANIMATE Superset.  E.g., Xerox, Gateway, IBM

vehicles   [mnemonic: COvehic]    [3 35 611]

Definition:   Types of transportation and conveyances used on land, sea or in air

Examples:    airplane, automobile, bicycle, canoe, carriage, missile, monorail, motorcycle, projectile, sailboat, schooner, ship, sled, sloop, spacecraft, taxi,   tractor, trailer, truck, van

Caution:   Proper names of vehicles, e.g. Buick, Concorde, may be included here.  However, words like Mercedes, Ford, which also denote the manufacturer, should be coded as proper organization names under the ANIMATE Superset.

meters   [mnemonic: COmeter]    [3 35 716]

Definition:    Devices that measure or regulate time, distance, speed, intensity, frequency, volume, flow, etc.

Examples:    clock, compass, gauge, micrometer, passimeter, penetrometer, radar, rangefinder, sonar, spectrometer, tensometer, thermostat, wristwatch

Caution:   Product names are included here unless the product name is identical with the company name, in which case the word should be coded as proper organization names under the ANIMATE Superset.

communication agents   [mnemonic: COcomm ]    [3 35 708]

Definition:    Devices for sending and receiving information

Examples:    cellular phone, fax, microphone, modulator, monitor, radio, receiver, short-wave, sonar, telegraph, telephone, television, telex, terminal, transmitter, walkie-talkie

Tips:   This subset narrowly defines devices for person-to-person communication rather than person-to-machine communication.

Caution:   Words like monitor, printer, scanner, recorder are more properly coded as machines/systems under CONCRETE Superset.

Product names are included here unless the product name is identical with the company name, in which case the word should be coded as proper organization names under the ANIMATE Superset.

undifferentiated agentive things   

[mnemonic: COundagt]    [3 35 248]

Definition:    Nouns denoting agentive concrete things which have not been covered by other categories within the agentive set.  

Caution:   Product names are included here unless the product name is identical with the company name, in which case the word should be coded as proper organization names under the ANIMATE Superset.

natural things    [mnemonic: COnat ]    [3 32]

Definition:    This set includes concrete things that exist in the natural world (not man-made objects) and which do not qualify as mass nouns.  These nouns are always count nouns which means that they cannot occur in the singular after quantifiers like more;  e.g., *more pebble, *more tree.  The one exception to this is the subset trees/wood which subsumes words like oak, pine and which can function as MASS Nouns; e.g., more oak.

This set has four subsets:

minute flora   [mnemonic: COflora]    [3 32 382]

Definition:   Diminutive concrete things that exist in the natural world; i.e., are not man-made objects

Examples:   alga, algae, spore 

Caution:   This set does not include minute animates, such as paramecium, flagella which should be coded as microscopic under the ANIMATE Superset.

plants   [mnemonic: COplant]    [3 32 383]

Definition:  Names of plants, flowers, weeds, brush, etc. 

Examples:  amaryllis, bindweed, blackthorn, blossom, carnation, clove, flower, lilac, nettle, pansy, plant, primrose, rose, vine, violet, weed

Caution:  If the plant is edible, it should be coded as edible under the CONCRETE Superset (e.g., beet) or, if a mass noun, like broccoli or rice, as mass edible under the MASS Superset.

Words like grass, wheat, flax, rye, being mass nouns (e.g., more wheat), should be coded as vegetative mass under the MASS Superset. 

trees   [mnemonic: COtree]    [3 32 384]

Definition:    Names of trees that do not also denote the wood.  These are count nouns (e.g., more poplars).  Words which denote both trees and wood can function as mass nouns (e.g. more oak).   

Examples:    hazel, holly, mimosa, palm, persimmon, piassava, poplar, willow

Tips:  To qualify for this category, the noun must not describe wood or food where the primary association is with wood (e.g., oak) or with food (e.g., olive). 

Caution:   Trees whose wood is a mass noun, e.g. more oak, should be coded as trees/wood under the CONCRETE Superset.

Words like orange, lemon, olive, grapefruit and pistachio denote both trees and food and, in the case of orange, lemon, and olive, also color.  If the primary association is the food, these words should be coded as edibles or edibles/color under CONCRETE Superset.

trees/wood   [mnemonic: COtrwd ]    [3 32 855]

Definition:    Names of trees whose wood is a Mass Noun (e.g. more oak).   

Examples:    ash, cedar, elm, fir, maple, oak, pine, redwood

Caution:   Trees whose wood is not a Mass Noun, e.g more poplars, should be coded as trees under the CONCRETE Superset.

Note that the word wood itself is encoded under the MASS Noun Superset.

miscellaneous natural things
[mnemonic: COmnat ]    [3 32 381]

Definition:    Nouns denoting natural things which have not been covered by other categories within the natural set.

Examples:   blade of grass, body, boulder, feather, gem, heavenly body, iceberg, leaf, pebble, petal, semi-precious stone, spider's web, splinter, sprig, stalactite, stalagmite, tendril, thorn, tree branch, tree trunk, whisker

Caution:   Nouns like Milky Way, Orion, mountain, volcano, earth, universe, galaxy, and North Star are coded under the PLACE Superset.

impulses/lights   [mnemonic: COlight]    [3 37]

Definition:    This set includes a wide variety of lights, light sources, and physical impulses.  It does not include animal/human impulses.

Examples:    beam, blinker, blip, bolt of lightning, bulb, candle, corona, display light, fault light, fireball, flame, flare, flash, flashbulb, flashcube, flashlight, flashing light, floodlight, gamma ray, gleam, glimmer, headlamp, headlight, highbeam, illuminator, impulse, indicator lamp, lamp, lantern, laser, laser beam, lightbeam, lightbulb, limelight, lightwave, kerosene lamp, meteor, microwave, neon sign, pilot light, pulse, radio waves, ray, reading lamp, search light, sound wave, spark, spotlight, streetlight, strobe light, taper, tail light, torch, tone, traffic light, ultrasound

Caution:   Light, sunlight, daylight, fire, display lighting, ambient light are coded as energy type under the MASS Superset.

Twilight is coded as a period of the day under the TIME Superset.

Celestial sources of light such as sun, moon, planets, stars, constellations, comets (but not meteors) are coded as geographical locations under the PLACE Superset.

Luminosity, luster are quality/property/nature under the ABSTRACT Superset.

Words like reflection and radiation are strong verbals under the ABSTRACT Superset.

marks/blemishes   [mnemonic: COmark ]    [3 44]

Definition:    Blemishes, defects, and marks both positive or negative in connotation.  This excludes medical conditions.

Examples:    beauty mark, birthmark, bloodstain, blot, blotch, bruise, burr, callous, canker sore, carbuncle, corn (ped.), crack, cyst, dimple, flaw, freckle, gash, goosebump, growth (med.), lesion, nick, pimple, pinhole, rash, rip, scab, scar, scratch, sear, smear, smudge, speck, speckle, splotch, spot, stain, stripe, stubble (light beard), sty, wart, wound, wrinkle

Tips:   These marks are non-informational.

Caution:   Medical conditions such as cancer, carcinoma, hernia are coded as states/conditions/relationships under the ABSTRACT Superset.

Words like watermark, tattoo, which convey information, are coded under the INFORMATION Superset.

edibles (non-mass)   [mnemonic: COednm]    [3 18]

Definition:   Anything edible or potable which does not have the properties of a mass noun.

Examples:   apple, banana, bagel, bean, beet, blueberry, candy bar, carrot, cookie, croissant, cucumber, cupcake, cutlet, delicacy, donut, dumpling, egg, fig, Fig Newton, fillet, frankfurter, fritter, garnish, hamburger, Hershey Bar, jellybean, leek, leftover, muffin, potato, potato chip, pork chop, sandwich, Twinkie

Caution:  If an edible thing has the properties of a mass noun, it should be coded as mass edible under the MASS Superset (e.g. broccoli, asparagus).

If an edible thing also describes a color, it should be coded as edibles/color under the CONCRETE Superset (e.g. orange, almond). 

edibles/color   [mnemonic: COedcol]    [3 18 855]

Definition:    Non-mass edible things which also denote colors.

Examples:    almond, cherry, lemon, olive, orange, walnut

classifiers   [mnemonic: COclass]    [3 39]

Definition:    A small set of terms that classify natural things and often occur with that thing in apposition; e.g., the constellation Orion.

Examples:   the compound chlorophyll, the constellation Orion, the element oxygen, the mineral alabaster, the planet Venus, the star Sirius

amorphous   [mnemonic: COamor]    [3 33]

Definition:   Real things, but without definite form and lacking distinct structure

Examples:   air pocket, biosphere,  blur, breath, breeze, crosscurrent, current, downdraft, draft, draught, eddy, flurry, fume, gale, halo, high (meteorological),  hurricane, ionosphere, low tide, monsoon, nebula, penumbra, plume, puddle, rainbow, shadow, storm, stratus cloud, surf, tide, tornado, torrent, tsunami, twister, typhoon, undercurrent, undertow, void, wave

Caution:   Words like mist, dew, fog, smog, wind, and rain, having the properties of mass nouns, are coded under the MASS Superset.

Atmosphere, because of its figurative use (lacking in atmosphere), is coded under the MASS Superset.

Words with strong verbal connotation like turbulence, surge, swell, ripple, occlusion should be coded as strong verbals under the ABSTRACT Superset.

Words with a strong geographic connotation like whirlpool, stream, water spout, terrain should be coded under the PLACE Superset.

atomistic   [mnemonic: COatom]     [3 19]

Definition:    Atomic and subatomic particles

Examples:    atom, boson, electrolyte, electron, fermion, graviton, isotope, lepton, meson, micelle, molecule, muon, neutrino, nucleon, nucleus, particle, photon, pion, positron, proton, quantum, quark, radical, tactoid, thermion

Caution:   Although mass and energy are interchangeable in high-energy physics, the Logos system distinguishes between particles and light waves, which latter are coded as impulses/lights under the CONCRETE Superset.

undifferentiated concrete things   

[mnemonic: COobj]    [3 03 212]

Definition:    Nouns denoting concrete things which have not been covered by other sets or subsets within the CONCRETE Superset.   

Examples:    bagatelle, curio, entity, find, humdinger, item, object, oddity, souvenir, thing, trifle

MASS Noun Superset  [mnemonic: MA]     [11]

Definition:   MASS Nouns denote a wide variety of physical things, such as money, grass, energy, food, steel, etc. that have a special property that distinguishes them from count nouns. This property is described below.

1.  Mass nouns commonly occur in the singular without articles (quantifiers), as in the following sentences: 

2.  Mass nouns, unlike count nouns, occur in the singular after quantifiers like any, enough, little, some, more, etc; e.g., some wine, enough sand, more gold.

Unlike mass nouns, count nouns following one of these quantifiers require a plural form:

The MASS Superset has the following sets:

Caution:  Some codes besides the MASS Superset have the mass noun property.  For example,

Use these rather than the MASS Superset in such cases.

Developers' Tips:    A unique subset code, remote mass  [mnemonic: remass]  [855] is available for assignment to any noun having mass noun characteristics where provision for such is not otherwise made in the superset to which it belongs.

raw materials/metals   [mnemonic: MAraw]     [11 38]

Definition:    Raw, solid materials out of which things are made

Examples:    canvas, down, fabric, glass, hide, iron, nickel, plastic, polyester, porcelain, rattan, rawhide, resin, rubber, satin, serge, sheepskin, sheet metal, silver, silk, slate, sterling silver, stone, stucco, tallow, timber, tin, wicker, wool

Tips:   The distinction between this set and functional mass can be seen in the distinction between glass and glassware.

You can distinguish between this set and minerals/solids by this simple test: Can some product be made of this material?  Typically, only raw materials/ metals satisfies this test.

Caution:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

functional mass   [mnemonic: MAfunc]     [11 49]

Definition:   Processed materials that have a clearly defined function

Examples:    cable, clothing, foam rubber, glassware, mucilage, muscle, papyrus, piping, putty, ribbon, rope, tableware, tape, tar, tarpaulin, tempera, thread, tile, tubing, wire

Tips:  The distinction between this set and raw materials/metals can be seen in the distinction between glassware and glass.

For words like computer memory or computer store, if the recording medium is a MASS noun, code the word here.  If the recording medium is a place, such as register, buffer, writing tablet, or notebook, code it as storage media for recorded data under the INFORMATION Superset . 

Caution:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

-gear/equipment      [mnemonic: MAgear]    [11 49 324]

Definition:    Noun phrases which have as their head noun the words gear or equipment.  As head words in such contructions, gear and equipment are mass nouns.

Examples:   camping gear, electronic equipment, fire-fighting equipment, fishing gear, radio equipment

Caution:  Depending on how the word gear forms the compound, the phrase may not be a mass noun at all, as in the case of helical gear or bicycle gear which should be coded as functional devices/tools under the CONCRETE Superset.

financial   [mnemonic: MAfina]     [11 97]

Definition:   Words denoting financial terms that have the properties of mass nouns.

Examples:   cash, collateral, change, coin, coinage, currency, income, lucre, money, petty cash, property, real estate, revenue, stock, treasure, wealth

Caution:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

Not all words dealing with finance are mass nouns obviously.  Words like dollar and cent are coded as units of money/value in the MEASURE Superset. 

Words like bond and insurance policy are coded as instructional data in the INFORMATION Superset.

Words that are both abstract concepts measured by unit under the MEASURE Superset (e.g, wealth, income, etc) and financial mass should be placed under the latter as the code with the higher priority.

energy   [mnemonic: MAener]     [11 23]

Definition:    Nouns denoting energy forces, naturally occurring or man made, and which have the properties of mass nouns.

Examples:   anti-matter, crosswind, current, electricity, fire, firepower, flux, force, friction, heat, horsepower, light, lightening, magnetism, manpower, nuclear power, radiation, solar energy, sound, sunlight, sunshine, traction, torque, wattage, wind, windage, windshear

Caution:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

vegetative   [mnemonic: MAvege]     [11 60]

Definition:    Nouns denoting vegetation that have the properties of mass nouns.  

Examples:   bark, fodder, grain, grass, kelp, moss, pasturage, raffia, seed, undergrowth, wheat

Tips:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

Caution:   Do not confuse with edible mass under the MASS Superset. 

Words that denote both trees and wood should be coded as trees/wood under the CONCRETE Superset.

animate mass   [mnemonic: MAanim]     [11 82]

Definition:   Living entities that have the properties of mass nouns

Examples:    bone, goatskin, gooseflesh, hair, hide, horsehair, marrow, mildew, mold, protoplasm, skin, tissue

Tips:   Be sure that your entry is not a count noun and has the properties of a MASS Noun.

Caution:   Words that denote both mammals and food or fur, (e.g., lamb, fox, duck) should be coded as mammals/food/fur under the ANIMATE Superset.

natural minerals/solids   [mnemonic: MAmine]    [11 84]

Definition:    Natural solid-state substances as opposed to liquids or gases

Examples:    alabaster, arsenic, asphalt. asbestos, bauxite, bitumen, chromite, clay, coal, coke, emery, fluorite, feldspar, gypsum, graphite, hail, lignite, meerschaum, mica, monazite, obsidian, ore, rock, sand, snow, sleet, silica, talc, uranium, zeolite

Tips:   You can distinguish between this set and materials/ metals by this simple test:  Can some product be made of this material?  Typically, only raw materials/ metals satisfies this test.

Caution:   If a mineral is a chemical compound or chemical agent, code it under those sets under the MASS Superset.

Be sure that your entry is not a count noun and has the properties of a MASS Noun.

chemical agents   [mnemonic: MAchem]    [11 83]

Definition:    Chemical substances that induce change

Examples:    adrenaline, aspirin, conditioner. fertilizer, fixative, germicide, glyceride, hardener, hemlock, herbicide, heroin, iodine, tannin, tenderizer, thinner

Tips:   Mass nouns that can be coded as both chemical agents and chemical compounds should be coded as chemical agents. 

Caution:   Be sure that your entry is not a count noun and has the properties of a MASS Noun.

chemical compounds   [mnemonic: MAcomp]    [11 52]

Definition:    Substances consisting of two or more different elements in definite proportions, not otherwise covered by the other sets in the MASS Noun Superset.

Examples:     ammonium, borax, chloride, chlorophyll, iron salt, raffinose, saltpeter, silver nitrate, sodium chloride, sulfide, talcum, vitriol,

Tips:  Mass nouns that can be coded as both chemical agents and chemical compounds should be coded as chemical agents. 

Caution:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

liquids   [mnemonic: MAliqu]    [11 45]

Definition:    Substances, natural or man made, in a liquid state. This category    includes liquid edibles.

Examples:    bile, blood, cocoa, coffee, gasoline, gravy, hot chocolate, lemonade, liquor, oil, perspiration, plasma, precipitation, rain, runoff, saliva, sap, schnapps, seawater, seltzer, seepage, soda, soup, tea, water, wine

Tips:   Be sure that your entry is not a count noun and has the properties of a MASS Noun.

edible mass   [mnemonic: MAedib]    [11 43]

Definition:    Edible non-liquid substances, natural or man made, including seasonings.

Examples:   cake, candy, cereal, chocolate, corn, dessert, flour, food, meat, mustard, parsley, pasta, pastry, pate, pepper, pie, pizza, rice, sage, salt, steak, stew, tarragon, tofu

Tips:   Be sure that your entry is not a count noun and has the properties of a MASS Noun.

Caution:   Edible liquids should be coded as liquids under the MASS Superset.

Non-mass edibles are to be coded edibles (non-mass) under the Concrete Superset.

gases   [mnemonic: MAgas]    [11 50]

Definition:    Substances in a gaseous state

Examples:    air, argon, butane, carbon dioxide, compressed air, ethane, ethylene, exhaust, fluorine, fog, fresh air, gas, helium, inert gas, krypton, mist, neon, oxygen, propane, smoke, steam, vapor, zenon,

Tips:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

wastes   [mnemonic: MAwaste]    [11 98]

Definition:    Mass nouns describing waste material, natural and man made

Examples:   breakage, carrion, chaff, dandruff, dross, garbage, rubble, rust,  scrap iron, scrap metal, sewage, slime, slosh

Caution:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

undifferentiated mass   [mnemonic: MAundif]    [11 20]

Definition:    Mass nouns which have not been covered by other categories within the MASS Superset.

Examples:   backfill, cargo, contraband, extract, fiber, foam, freight, frost, froth, fuzz, lint, kitsch, laundry, loot, paraphernalia, powder, salve, scarring, shading

Caution:  Be sure that your entry is not a count noun and has the properties of a MASS Noun.

ANIMATE Noun Superset   [mnemonic: AN]    [5]

Definition:  Includes all animate beings, human and non-human, designated singly or by groups.  It also includes spiritual entities; e.g., deity, angels, etc.

Animate nouns are comprised of the following sets: 

Some of these sets have subsets. 

Designations/professions has the following subsets:

Human collectives has a single subset:

Non-human animates has the following subsets:

designations/professions   [mnemonic: ANdes]    [5 91]

Definition:   Nouns denoting professions or other human designations

Examples:   accompanist, accomplice, account executive, activist, adolescent, aide, author, boy, Buddhist, buddy, buyer, chairperson, child, colleague, consultant, congressman, corpse, deceased, descendent, duo, ecologist, fatality, girl, grandmother, helper, heroine, husband, individual, judge, lawyer, legatee, lessee, liaison, man, millionaire, mother, mummy, nonentity, nurse, offspring, orphan, outsider, pacifist, patient, perpetrator, person, pianist, postmaster, postmodernist, prelate, physician, physicist, poet, Republican, rhetorician, scientist, self, seller, soul,  subscriber, tourist, translator, uncle, wife, woman

Caution:   Words like chairman, professor, general, president are coded professions/designations when all lower case, but as titles when entered with an initial cap.   

Words like French, Russian, Chinese that designate both people and language should be coded in the people/language subset of the present set.

Note that while person is coded here, people is coded as a human collective.

titles   [mnemonic: ANtitle]    [5 91 807]

Definition:    Titles of individual human beings, but not of organizations

Examples:   Baron, Brigadier, Chancellor, General, Chairman, Dr., Lady, Lord, Marquis, Mr., Mrs., Ms., President, Prince

Tips:  Titles always have initial caps.

Caution:   Words like President, General, Chairman, when used without initial caps, should not be coded here but as professions/designations.

people/place   [mnemonic: ANplace]    [5 91 205]

Definition:   Designations for people in terms of place that do not simultaneously describe a language

Examples:   Afghan, American, Arab, Berliner, Briton, Canadian, Colombian, Detroiter, Dubliner, Dusseldorfer, European Hamburger, Irishman, Kosovar, Mexican, Montrealer, New Yorker, Pole

Caution:   Words like Japanese, German, Albanian, etc, should be coded as people/ language under the set professions/designations.

people/language   [mnemonic: ANlang]    [5 91 206]

Definition:    Designations of languages that simultaneously denote the people who speak them

Examples:   Albanian, Armenian, Bulgarian, Chinese, English, German, Japanese, Norwegian, Russian, Spanish

Caution:   Words like British, Canadian, Argentinean, European do not describe languages and should be coded people/place under professions/designations.

proper names (people)  [mnemonic: ANname]    [5 91 207]

Definition:   Given names and surnames

Examples:   Baudelaire, Dante, John, Jones, Mary, Smith, Shakespeare, Socrates

Tips:   By proper names here is meant family names, given names, nicknames, etc.  It does include proper nouns like Buddhist, Libertarian, etc.

human collective   [mnemonic: ANcoll]     [5 94]

Definition:   Nouns denoting human collectives

Examples:    agency, army, bureau, business, committee, company, corporation, cult, enemy, executive committee, faculty, garment industry, governing body, inspectorate, judiciary, labor union, meritocracy, membership, militia, membership, monarchy, navy, people, postal administration, publisher, search party, service industry, staff, stock company, task force, threesome, throng, tribunal

Caution:  Words like office, school, kindergarten should be coded as functional locations under the PLACE Superset.

Proper names of human collectives (e.g., Congress, Parliament) should be coded as proper organization names.

proper organization names  [mnemonic: ANorg]    [5 94 193]

Definition:    Proper names of established organizations

Examples:    Airbus, Amtrak, American Medical Association (AMA), Congress, FBI, Ford, Gateway, IBM, Kremlin, Logos, Mercedes-Benz, Microsoft, NASA, OPEC, Parliament, Reuters, Supreme Court, Toyota

Tips:   These words always have initial caps.

Caution:   Words like Washington, Wall Street, White House which are strictly speaking not proper names of organizations (but which have a human collective connotation) and also denote places, should be coded under the PLACE Superset.

Organizational names which are also used to denote products (e.g., Toyota, Ford, Mercedes, IBM, Xerox, Logos) should be coded here rather than under the code for the thing they represent. 

It is usually not possible to distinguish between product name (IBM) and company name (IBM) on the basis of subject matter codes (SMC) because a text with that subject matter would typically use the word in both ways.  Therefore, a choice has to be made, in this case, in favor of the company that produced the product.

non-human animates   [mnemonic: ANanim]      [5 51]

Definition:    All species of living entities from micro-organisms to mammals, excluding humans and human organizations

This set includes the following subsets: 

non-human aggregate   [mnemonic: ANaggr]     [5 51 208]

Definition:    Terms for non-human aggregates

Examples:    bevy, brood, colony, covey, flock, fold, gaggle, herd, hive, horde, litter, menagerie, pack, pride, school, swarm

Caution:   Words like school, pride, horde, pack, whose primary meaning is otherwise, should only be coded here with an appropriate subject matter code at time of entry in TermBuilder.   

mammals  [mnemonic: ANmamm]    [5 51 126]

Definition:    All warm-blooded vertebrate animals, humans excepted

Examples:   anteater, antelope, bear, bronco, caribou, cat, dachshund, deer, dog, elephant, gelding, German Shepherd, giraffe, Hereford, Pekinese, lapdog, lion, nag, pup, seal, weasel

Tips:   This whole category should be treated as remote mass.  The reason is that the designation for food taken from these animals is most usually a mass noun.

Caution:   Terms for mammals like lamb, deer, that also denote food, and terms like seal, fox, that also denote fur or hide, can also function syntactically as mass nouns.  Such terms must be coded mammals/food/fur in order to capture this mass noun property (e.g. more lamb, more fox).

mammals/food/fur  [mnemonic: ANmammfd]    [5 51 855]

Definition:    Words for mammals that denote food, fur or hide, and that therefore are able to function as mass nouns in these contexts (e.g. some lamb, some fox).

Examples:    deer, fox, lamb, rabbit, seal

fowl  [mnemonic: ANfowl]    [5 51 125]

Definition:   Designates every type of bird, domestic or wild

Examples:   canary, dove, drake, eagle, egret, gull, hawk, heron, kingfisher, kiwi, lark, magpie, penguin, pigeon, robin, sparrow, stork, swan, swift, tern, thrush, vulture, woodlark, woodpecker

Caution:   Words like duck, quail, chicken, pheasant, turkey, capon, etc. which denote both birds and food and should be coded fowl/food.

fowl/food  [mnemonic: ANfowlfd]    [5 51 855]

Definition:    Words for fowl that also denote food and are able to function as mass nouns in that context (e.g. some chicken, some duck).

Examples:   capon, chicken, duck, goose, pheasant, quail, squab, turkey

fish  [mnemonic: ANfish]    [5 51 124]

Definition:   Designates cold-blooded aquatic vertebrates

Examples:    bass, bluefish, grouper, haddock, halibut, hammerhead, herring, kipper,   lobster, mackerel, mussel, oyster, perch, salmon, sardine, shark, shrimp, snapper, sole, sturgeon, tadpole, tilefish, trout, whiting

reptiles  [mnemonic: ANrept]    [5 51 123]

Definition:   Designates cold-blooded, egg-laying vertebrates

Examples:   alligator, asp, boa, crocodile, dinosaur, frog, iguana, lizard, python, reptile, snake, tortoise, turtle

bugs/insects  [mnemonic: ANbugs]    [5 51 122]

Definition:   Designates every type of insect

Examples:  ant, bee, butterfly, caterpillar, centipede, cicada, cricket, dragonfly, fly, gnat, ladybug, mosquito, moth, pest, roach, spider, termite

micro-organisms  [mnemonic: ANmicro]    [5 51 121]

Definition:    Terms that designate microorganisms. 

Examples:    amoeba, bacteria, cell, chromosome, corpuscle, dendrite, flagella, fungus, gamete, gene, germ, leukocyte, microorganism, microbe, neuron, parasite, paramecium, pathogen, spirochetevirus

other animate  [mnemonic: ANother]    [5 51 213]

Definition:    Animate designations that are not covered in other subsets of the ANIMATE Superset.

Examples:  angel, apparition, cherub, clone, creature, deity, dragon, ghost, goblin, gnome, goddess, leprechaun, mermaid, monster, nymph, pet, sphinx, unicorn

PLACE Noun Superset  
[mnemonic: PL]   [9]

Definition:    Nouns denoting place, geographical entities, and geographical locations.

Sets within the PLACE Superset are:

Tips:   PLACE Nouns are distinguished from CONCRETE Nouns by their human scale. Thus, words like box, drawer are receptacles under CONCRETE Superset; words like parlor, shed are enclosed spaces under PLACE Superset.

PLACE Noun coding reflects two important distinctions:  (1) agentive/non-agentive and (2) proper name/common noun.  In combination, these are:

Since PLACE Noun codes are mutually exclusive, the coder should experience no difficulty with coding priorities here.

Caution:   In coding PLACE Nouns, be mindful of the possible presence of an agentive property of a word (e.g. the agentive city vs. the non-agentive cliff).   If this property exists in your entry, be sure to select the appropriate agentive subset if one exists.  E.g., city would be coded agentive unnamed geog. locations.

Some words which might appear to belong to the PLACE Superset also have other meanings which may require their being given a different code.  For example, property should be coded properties/qualities/nature under ABSTRACT Superset, that being the more fundamental meaning of property. Riverfront property, on the other hand, lacks this ambiguity and is indeed a PLACE Noun.

A number of words have multiple meanings only one of which is PLACE. In many cases, the other meanings take precedence.  For example:

--property should be properties/qualities/nature under ABSTRACT Superset
--cell should be microorganism under ANIMATE Superset
--parcel should be undiff.  concrete object under CONCRETE Superset
--domain should be field of knowledge under INFORMATION Superset
--clearance, emplacement, excavation, crossing, claim should be strong verbal        under ABSTRACT Superset

Any of the above can, of course, be coded as PLACE Noun if modified; e.g. riverfront property, railway crossing, gun emplacement, etc.  Also, the assignment of subject matter codes (SMC) at time of entry via TermBuilder can determine the code of a noun in one direction or another.

functional locations
[mnemonic: PLfunc]    [9 26]

Definition:    Names of locations where a specific function is performed.   

Examples:    airfield, airdrome, amphitheater, anchorage, arena, arsenal, barber shop, battlefield, battleground, beauty parlor, bullring, campgrounds, campsite,  cleaners, confectionery, construction site, control point, courtroom, diner, delicatessen, depository, dock, dormitory, drilling platform, drugstore, dumpsite, farmyard, fish market, garage, gas station, gymnasium, hostel, hothouse, icehouse, junkyard, kitchen, landing field, launching site, shelter, spa, theater

Tips:   Words in this set do not typically function as human agents.  For example, one would not expect to hear:
      The dock plans to expand its operation.  
      The graveyard announced a new policy. 

Terms which can be used as human agents, (e.g. university, bank, factory, academy, airport, armory, arsenal, hospital, nursing home, etc.) should be coded as functional locations (agentive)

agentive functional locations
[mnemonic: PLagfunc]    [9 26 228]

Definition:   Names of locations where a specific function is performed.   Words in this subset can also function in the capacity of human agents; e.g., as subjects of verbs like think, plan, intend, etc.

Examples:   abbey, academy, airport, air base, bank, bureau, depot, dispensary, factory, fire station, hospice, hospital, museum, office, post office, school, shipyard, spa, supermarket, university, Wall Street, White House

Tips:   These terms can frequently be used to denote human agents; for example:
               The university has decided to hire a new instructor.   
               The bank has announced new business hours for the summer.

enclosed spaces  
[mnemonic: PLencl]    [9 27]

Definition:    Physical space on the human scale which has the sense of being enclosed

Examples:    abode, accommodations, adobe, alcove, annex, anthill, apartment, arbor, arcade, boudoir, booth, cabin, cellar, chateau, closet, coop, dungeon, dormitory, foyer, grave, hangar, homestead, house, hovel, hut, kennel, lobby, lounge, manor, pantry, room, salon, shed, shop, suite, turret, vault, veranda        

Tips:   When the preposition from precedes nouns in this set, the preposition has the sense of out of.  For example:
          Crowds flowed from the theater. 
          The celebrity came from her apartment.

Caution:   Accommodations (pl) is an enclosed space, but in the singular it should be coded as a strong verbal.  

The line between enclosed spaces and functional locations may sometimes seem arbitrary. If the term seems to emphasize functionality, such as delicatessen, workshop, convent, it should be coded as functional locations.

paths  
[mnemonic: PLpath]    [9 55]

Definition:   Places that have the general structure of a path

Examples:   canal, channel, corridor, hallway, orbit, path, railway, river, road, stream, straits, subway, trajectory, tributary

Tips:   This subset should not be confused with conduits under the CONCRETE Superset.   The distinction has to do with the human scale of paths.

Although in some sense a path, words like bridge, trestle, ramp, etc. should be coded as links under CONCRETE Superset and not here under paths despite the human scale of both.   This is because bridges are concrete things in a way that paths are not.   Conversely, a path is geographical in a way that a bridge is not.

non-agentive common-noun geog. locations
[mnemonic: PLnagcom]    [9 29]

Definition:   General geographical locations which are not proper names and which are non-agentive in nature.

Examples:   bay, beach, border, coast, countryside, forest, frontier, hemisphere, neighborhood, ocean, sky, upper airspace

agentive geog. entities  
[mnemonic: PLaggeo]    [9 94]

Definition:   These are geographical entities with proper names.

Caution:   Place names like France, New York, Ontario comprise a country/ state/ province subset under PLACE Superset, but share a set code with human collective of the ANIMATE Superset. This anomaly occurs because of the identification of a country with its people. E.g., France produces great wine.

countries/states/provinces  
[mnemonic: PLcoun]    [9 94 230]

Definition:   Proper names of countries, states, provinces.  These are agentive by definition.

Examples:    Australia, Brazil, California, Ecuador, England, Florida, France, India, Nigeria, Ontario, Poland, Quebec, Sicily, Tasmania

cities 
[mnemonic: PLcity]    [9 94 226]

Definition:    Proper names of cities.  These are agentive by definition.

Examples:   Calcutta, London, Paris, Rome, St. Petersburg, Tokyo, Washington

agentive common-noun geog. entities
[mnemonic: PLagcom]    [9 94 236]

Definition:   Terms for geographical locations which are not proper names and which are often used to denote human agents (e.g., the city plans to......).

Examples:   borough, city, county, country, district, duchy, earldom, emirate, empire, kingdom, municipality, precinct, province, republic, state, town, township village

Tips:   Entries here are always common nouns.  Entries which are proper names of geographical locations are coded under their appropriate "named" subset in the PLACE Superset. 

non-agentive proper geog. entities
 [mnemonic: PLnagprop]    [9 56]

Definition:   These are non-agentive geographical entities with proper names.

continents 
[mnemonic: PLcont]    [9 56 227]

Definition:   Proper names for the continents.  These are non-agentive by definition.

Examples:   Africa, Antarctica, Asia, Europe, North America, South America

bodies of water 
[mnemonic: PLwater]    [9 56 229]

Definition:    Proper names of any type of body of water.  These are non-agentive by definition.

Examples:   Amazon River, Atlantic Ocean, English Channel, Gulf of Mexico, Great Lakes, Hoover Dam, Hudson Bay, Lake Tahoe, Mediterranean Sea, Niagara Falls, Panama Canal, Suez Canal, Straits of Gibraltar

other non-agentive proper geog. entities
[mnemonic: PLothprop]    [9 56 238]

Definition:    Proper names of miscellaneous geographical places. These are non-agentive by definition.

Examples:   Arctic Circle, Blarney Stone, Cape Horn, Far West, Great Dividing Range, Great Wall of China, Hawaiian Islands, Mt. Fuji, Plymouth Rock, Rocky Mountains, Stonehenge, Swiss Alps, Taj Mahal, Yellowstone National Park, Yosemite

undifferentiated place nouns  
[mnemonic: PLundif]    [9 57]

Definition:   Nouns denoting place of a very general nature which have not been covered by other categories within the PLACE Superset.

Examples:   area, birthplace, crevasse, corner, environment, expanse, field, glade, heaven, highland, hotspot, inferno, junction, landscape, locale, locality, pasture, position, region, ridge, rise, scarp, scene, seaside, setting, shoal, sinkhole, site, space, vacancy, zone

INFORMATION Noun Superset  
[mnemonic: IN]    [12]

Definition:    The INFORMATION Noun Superset is comprised of nouns that denote data, information, or knowledge. This category also includes the medium on which the information is recorded, represented or communicated;  i.e., spoken, written, dramatized, sung, etc. 

Sets and subsets within the INFORMATION Noun Superset are as follows:

Caution:   Many nouns that denote physical objects that would seem to belong to the CONCRETE Noun Superset should actually be coded as INFORMATION Nouns;  e.g. newspaper, map, paperback, dictionary, floppy disk, cassette, etc.

instructional/legal  
[mnemonic: INinst]    [12 74]

Definition:    Nouns that designate policy, directions, orders, commands, etc.

Examples:    affidavit, branch, bylaw, certificate, charter, contract, covenant, direction, directive, edict, guarantee, instruction, law, manual, norm, notice, order, prescription, prophecy, protocol, recipe, rule, schedule, standard, statute

Tips:    Words in this set tend to have an agentive character;  e.g., the statute requires that . . .;  the regulation calls for. . . .  Thus, these terms tend to have a hortatory or regulatory character rather than a mere descriptive or informational character. 

Terms like line of code, program instruction, hyperlink, hot button, branch instruction, Do Loop should be coded here as instructional data and not as software under CONCRETE Superset.

Terms like web page, web site should be coded as recorded data under INFORMATION Superset.    

Terms like URL, ASCII, HTML, JAVA should be coded as symbolic data under INFORMATION Superset.

games/rituals 
[mnemonic: INgame]    [12 74 224]

Definition:    Games or rituals performed according to written rules

Examples:   baseball, basketball, chess, cards, checkers, dominoes, football, hockey, lacrosse, liturgy, lottery, poker, rugby, vespers

symbolic data  
[mnemonic: INsymb]    [12 75]

Definition:    Nouns that denote information or knowledge recorded in symbolic form

Examples:   address, algorithm, alphabet, asterisk, backslash, cedilla, circumflex, character, chord, code, coefficient, colon, conjunction, determiner, ellipsis, flat,   formula, hyphen, infinitive, language, letter, noun, number, parameter, octave, qualifier, radical, sharp, signal, staff, typeface, variable, verb, vowel

Tips:    Terms like URL, ASCII, HTML, JAVA should be coded here as symbolic data.

Terms like web page, web site should be coded  as recorded data under INFORMATION Superset.

recorded data  
[mnemonic: INdata]    [12 76]

Definition:    Nouns that denote information or knowledge that has been recorded

Examples:   album, artwork, atlas, best seller, biography, book, brochure, calendar, casebook, data sheet, diary, dictionary, dossier, engraving, essay, flowchart, graph, leaflet, letter, manuscript, map, message, newspaper, paperback, placard, picture, portfolio, registry, script, sentence, telegram

Tips:   Terms like web page, web site should be coded here as recorded data.

Terms like URL, ASCII, HTML, JAVA should be coded as symbolic data under INFORMATION Superset.

scripted events 
[mnemonic: INevent]    [12 76 223]

Definition:   Nouns that denote data, information, knowledge, etc. imparted in a specific moment of time through speaking, writing, dramatization, song, etc., and usually recorded in a script or score.

Examples:  aria, cinema, cantata, concert, farce, homily, lecture, movie, operetta, oratorio, overture, pantomime, postlude, radio program, recital, revue, sermon, speech, symphony, TV show

Tips:   Because of their informational content, words such as sermon, homily, lecture, concert, recital should be coded here as scripted events rather than as time events under the ABSTRACT Superset. 

Caution:   The distinction between scripted events and the arts may seem arbitrary in some cases;   e.g., opera is coded under the arts, and operetta is coded under scripted events.  The justification for this is that opera denotes a field of study as well as an event, whereas operetta would seem to denote only a scripted event.  The same can be held true for drama vs. movies; for poetry vs. recital, etc.

evidence/symptoms 
[mnemonic: INevid]    [12 96]

Definition:    Nouns denoting evidence, indications, symptoms, signs.

Examples:   auspice, clue, cue, evidence, example, hint, portent, premonition,  proof, sighting, signal, symptom, syndrome

Caution:  Words like diagnosis, prediction should be coded as strong verbals under ABSTRACT Superset because of their pronounced verbal coloration.

fields of knowledge   
[mnemonic: INknow]    [12 78]

Definition:   Nouns that denote fields of knowledge, study, research, etc., including specialty fields and hobbies

Examples:   agriculture, botany, chemistry, criminology, crystallography, cybernetics, data processing, ecology, forestry, genetics, geriatrics, heuristics, history, hydrology, linguistics, medicine, mineralogy, philately, philosophy, photography,   psychology,technology, topography, typography, zoology

the arts 
[mnemonic: INarts]    [12 78 225]

Definition:    Nouns that denote spoken, written, dramatized, sung or similarly presented material within the sphere of the arts

Examples:   acrobatics, ballet, calypso, comedy, drama, folk music, jazz, judo, karate, melodrama, music, opera, poetry, sumo, swing, tragedy

Caution:   The distinction between the arts and  scripted events may seem arbitrary in some cases;  e.g., opera is coded under the arts, and operetta is coded under scripted events.  The justification for this is that opera denotes a field of study as well as an event, whereas operetta would seem to denote only a scripted event.  The same can be held true for drama vs. movies; for poetry vs. recital, etc.

storage media for recorded data
  [mnemonic: INstor]    [12 77]

Definition:    Nouns that designate places where data may be stored

Examples:   buffer, boot disk, cartridge, cassette, CD ROM, data base, disk, file, floppy disk, general ledger, hard disk, magnetic tape, microfiche, notepad, page, print library, register, tablet, tape reel, workstation file

Tips:   If the recording medium is a place, such as register, buffer, writing tablet, or notebook, code it in this category.  If the recording medium is a mass noun, such as computer memory or computer store, code the word as a functional mass in the MASS Noun Superset.

undifferentiated information 
 [mnemonic: INundif]    [12 79]

Definition:    Nouns denoting information which have not been covered by other categories within the INFORMATION Superset.

Examples:   adage, background course, background fact, cliche, filetalk, in-depth knowledge, information, specifics, subject, topic

ABSTRACT Noun Superset  
[mnemonic: AB ]    [6]

Definition:    The ABSTRACT Noun Superset contains three sets of abstract nouns.  These are:

verbal abstracts describes procedures, behavior, actions and persons/things as agents.  non-verbal abstracts describes qualities, conditions, and relationships of things or persons as non-agents (patients).  This set also includes concepts relating to classifications of things/persons and source or origin of things/persons.  general concepts pertain to such general ideas as as justice, Buddhism, etc. 

Priority for parsing purposes is verbal, non-verbal and general, in that order. Note that verbal abstracts often take verbal complementation. To illustrate, note  how differently the verbal and non-verbal abstracts codes function in the following sentences.  

(1)   There are three ways of cooking lentils. 

(2)  There are three types of cooking utensils.

In (1), the abstract noun ways is a verbal abstract because it takes a verbal complement (cooking is a verb here).

In (2), the abstract noun types is a non-verbal abstract, and as a consequence cooking here is interpreted by the parser as an adjective.

verbal abstracts  (re processes, behavior, persons as agents)  
 [mnemonic: ABverb]    [6 41]

Definition:    Verbal abstract nouns are so-called because they (1) anticipate a verbal complement (e.g., procedure for editing text);  (2) denote a time event (e.g., birthday party); (3) denote a process, action or result of same (e.g., noise abatement). 

The verbal abstract subsets are as follows:

Tips:   A noun may be coded as a verbal abstract if it can introduce a verbal complement, as in the following constructions:

How used:  Verbal abstract codes tell the translation system to expect a possible verbal complement to the right of the noun.  For example, in the phrase, Her ease in handling the situation was..., the verbal abstract code for ease enables the system to recognize that in handling the situation should be attached to ease, thus treating the entire phrase as NP

purpose 
[mnemonic: ABpur]    [6 41 748]

Definition:    Abstract nouns denoting purposes, intentions, objectives, goals, and which take a verbal complement.

Examples:    function, mission, objective, problem, task

How used:   As pre-verbal to constructions such as to verb, of v'ing, in v'ing

Tips:   A noun may be coded purpose if it can introduce a verbal complement, as in the following constructions:

NOUN [ABpur] + TO + INFINITIVE as in mission to do s.t. 

NOUN [ABpur] + OF + V'ING as in task of doing s.t.. 

NOUN [ABpur] + IN + V'ING as in objective in doing s.t.

Caution:   If your entry is a compound that already includes the verbal complement (e.g., equation solving problem, computing task, revision function), then it should not be coded as purpose, but as undifferentiated verbal abstract [ABverb].

method/process/procedure 
[mnemonic: ABmeth]    [6 41 733]

Definition:    Abstract nouns denoting methods, means, etc. and which take a verbal complement.

Examples:   manner, means, method, mode, plan, technique, way

How Used:   As pre-verbal to constructions such as for v'ing, of v'ing, to verb 

Tips:  A noun may be coded method/process/procedure if it can introduce a verbal complement, as in the following constructions:  

NOUN [ABmeth] + FOR = V'ING as in method for doing s.t.

NOUN [ABmeth] + OF + V'ING as in way of doing s.t.

NOUN [ABmeth] +TO +  INFINITIVE as in means to do s.t.

Caution:   If your entry is a compound that already includes the verbal complement (e.g., equation solving method, computing mode, revision plan), then it should not be coded as method, but as undifferentiated verbal abstract [ABverb].

cause/potential/disposition 
[mnemonic: ABcause]    [6 41 602]

Definition:    Abstract nouns that describe cause, reason, motivation, readiness, etc.; i.e., cause, potential or disposition for action and which take a verbal complement.

Examples:    ability, basis, effort, factor, interest, mind, motivation, patience, perseverance, persistence, power, readiness, reason, reluctance, right, sense, skill, suitability, talent, urgency

How Used:   As pre-verbal to constructions such as for v'ing, to verb

A noun may be coded cause/potential/disposition if it can introduce a verbal complement, as in the following constructions:

NOUN [ABcause] + FOR + V'ING as in basis for doing s.t.

NOUN [ABcause] + TO + INFINITIVE as in reason to do s.t.

Caution:   Words like patience, perseverance, persistence belong under this subset rather than under quality of action/agent, which follows. This is because cause/potential/disposition abstracts can be complemented with to verb, whereas quality of action/agent nouns (efficiency, ease, brevity) can only be complemented with in v'ing.

quality of action/agent 
[mnemonic: ABqual]    [6 41 655]

Definition:    Abstract nouns describing the quality of an action, process, or the   one acting, and which take the specific verbal complement in v'ing.  E.g., accuracy in coding. 

Examples:    accuracy, aggressiveness, brevity, ease, efficiency, industriousness, playfulness, rapidity, suitableness, tenacity

How Used:   These nouns take in v'ing complements.

Tips:   Nouns in this category describe the quality of an agent or action.  They often answer the question: "How does s/he do it?" 

A noun may be coded in this subset if it can introduce the verbal complement in v'ing, as in the following:

NOUN [ABqual] + IN + V'ING as in rapidity in doing s.t.

Caution:  If the noun in question can also be complemented by an infinitive clause, it does not belong here, but most probably under cause/potential/disposition.   This applies to nouns like patience, perseverance, persistence, etc.  E.g., They had the patience to master the method.  They had the skill to do the job. 

negative causes 
[mnemonic: ABnegc]    [6 41 764]

Definition:    A narrow class of abstract nouns that describe causes, dispositions that are negative in their effect, and which take the complements of v'ing and/or to verb.  This is a negative variant of the cause/potential/ disposition subset.

Examples:   burden, cost, danger, fear, ordeal, peril, reluctance, risk, threat

How Used:   As pre-verbal to constructions such as to verb, of v'ing. 
E.g., danger of collapsing;  threat of being attacked;  risk of hurting someone;  fear of flying;  burden of proving innocence;  reluctance to comply;  ordeal of losing weight, etc.

Tips:   Nouns in this subset usually answer the question why a thing should not be done.

Nouns in this subset may introduce a verbal complement, as in the following constructions:

NOUN [ABnegc] + TO + INFINITIVE as in a threat to do s.t.

NOUN [ABnegc] + OF + V'ING as in the risk of doing s.t.

Caution:   If the noun in question is already modified by a verbal complement, e.g., building costs, war threat, it should not be coded here, but probably under strong verbals below.

strong verbals: actions/processes/behavior or the result of same
[mnemonic: ABstrvb]    [6 41 749] 

Definition:    A broad class of nouns or noun phrases that denote an action, process, behavior or result of same. Strong verbals that govern prepositions, as illustrated below, take codes reflecting their governance (not including of however)  (See Prep Governance chart below.)

Strong verbals should not be confused with PROCESS Nouns. (See "Caution" below.)

The basic distinction between PROCESS Nouns and strong verbals is that PROCESS Nouns (e.g., indication) are convertible to verbs in certain constructions; (e.g., make an indication = indicate).  PROCESS Nouns are always single words.  Whenever the entry of a  PROCESS Noun contains an adjective or other noun modifying it, meaning, in effect, that it cannot be converted to a verb, that entry becomes strong verbal by definition.

Examples of strong verbals that do not govern prepositions: 

Strong verbals derived from the -ing verb form:
board meeting, default sorting, dial pulsing, digital switching, information processing, hard disk partitioning, information processing, schedule planning, tape file processing, video conferencing

N.B. All single word -ing entries must be coded as PROCESS Nouns.  In order for an -ing form to qualify as a strong verbal, it must be modified, that is, must be a noun phrase.  

Examples of strong verbals derived from the verb infinitive:
Big Bang, buy, cable transfer, coffee break,  congressional veto, data control, data exchange, dichotomizing search, dig, discard, dodge, dole, drink, economic forecast, forms control, grammar check, guess, long distance call, memory lapse, on-line help, pay cut, phone call, programming change, triple click, vow

Examples of strong verbals expressing result of action, process, behavior:
bargain, military build-up, charge-back, coup, data entry, dispersal, Doppler effect, early checkout, financial oversight, hypnosis, mix, misconduct, mistrial, motion, mount/ dismount operation, outlay, outlook, ovation, retrofit, snow removal, startup, suicide, systems backup, takeoff, traffic, water storage

N.B.  All of the above strong verbals bear the same code.  On the other hand, the strong verbals in the box below govern prepositions and take codes to reflect their governance.  E.g., food distribution (to);   money transfer (to);  merger (with);  outlook (on). 

Caution:   Do not confuse strong verbals with PROCESS Nouns (e.g., amendment, illustration, absorption).  Unlike PROCESS Nouns, strong verbals cannot be transformed back into verbs. When PROCESS Nouns like absorption and distribution are modified (e.g. heat absorption, dividend distribution), they cannot transform back into the verb from which they derive;  hence, they become strong verbals.  Other types of strong verbals are those nouns which are strongly verbal but don't come from a verb.  For example, shutdown is an action, but shutdown is not a verb.

Be sure to consider the preposition governance of strong verbals, as these codes are critical to parsing.  Do not consider the preposition of in this connection however, as it is almost always genitival, introducing the subject or object of the verbal rather than a true complement.

time events 
[mnemonic: ABtime]    [6 41 732]

Definition:    Abstract nouns that denote events or happenings in time

Examples:    birthday party, Christmas, convention, end time, feast, holiday, instance, moment, pageant, parade, pause, picnic, stop time, wedding reception

Tips:   A word falls into the category of time events if it qualifies as follows:

Caution:   Words which have explicit verbal content, such as disarmament, disbarment, disinheritance, fireworks, fistfight, forfeiture, groan, happening, hatching, hitting, hookup, horseplay, internment, job execution, rehearsal, pilgrimage, layoff, libation, though they occur in time should not be coded as time events, but as strong verbals.

Because of their informational content, words such as sermon, homily, lecture, concert, recital should be coded as recorded events under the INFORMATION Superset.

Words like miracle, phenomenon do not satisfy the fixed/focused time conditions cited above and should be coded as strong verbals.

contrary events 
[mnemonic: ABcont]    [6 41 765]

Definition:    A very restricted class of abstract nouns that designate an event or happening contrary to the expected and can be used in the context make provision for to mean take precaution against.

Examples:    accident, blizzard, catastrophe, disaster, error, navigation error, power surge, theft

How Used:   If constructions like make provision for X have the meaning take precaution against, then X = a contrary event noun.   E.g., This system makes provision for spelling errors = This system takes precaution against spelling errors. 

Tips:   A noun need not indicate a catastrophe or accident to be classified as a contrary event, but simply be an event contrary to the expected, such as overflow.

Caution:   Words like pandemonium, bedlam, panic, pestilence, plague, pile-up, although contrary do not satisfy the condition cited above that make provision for means take precaution against.  This subset should only be used in the restricted sense described above.

undifferentiated verbal abstracts
(re processes, behavior, persons as agents)  
[mnemonic: ABverb]    [6 41 41]

Definition:    Nouns denoting verbal concepts which do not fall within the other subsets of verbal abstracts.

Examples:    acting technique, computing task, distribution processs, error- correction procedure, fact-finding mission, reading readiness, navigation skill, writing talent

Tips:   Note that in the examples above, the head noun would normally be coded elsewhere under verbal abstracts were it not for the fact of their verbal modification.   

Caution:   Be sure to bear in mind the point given in the tip above when coding compound nouns under verbal abstract subsets. 

This distinction is important so that the system will not misconstrue the verbal clauses in the following sentences:
      (1)  He developed new error-correcting procedures to lower costs.
      (2)  She studied acting techniques to advance her career.
      (3)  She developed a new procedure to prioritize tasks.
In (1) and (2), the particle to has the sense of in order to.  If procedures and techniques in these sentences had been coded as method/process/procedure, the system would have seen the verbal clause as complementary to the noun, as in (3), rather than as adverbial to the sentence in effect,and therefore would not have have assigned the sense of to to the particle in order to.

In many target languages, e.g, French and German, this distinction is obviously very critical to the translation.

non-verbal abstracts (re things, persons as non-agents)  
 [mnemonic: ABnonvb]    [6 40]