A TAXONOMY FOR ENGLISH NOUNS AND VERBS
Robert A. Amsler Computer Sciences Department University of Texas, Austin. TX 78712
ABSTRACT: The definition texts of a machine-readable First, the data shoul'd provide information on the pocket dictionary were analyzed to determine the contents of semantic domains. One should be able to disambiguated word sense of the kernel terms of each determine from a lexical taxonomy what domains one word sense being defined. The resultant sets of word might be in given one has encountered the word pairs of defined and defining words were then "periscope", or "petiole", or "petroleum". computaCionally connected into t~o taxonomic semi- lattices ("tangled hierarchies") representing some Second, dictionary data should be of use in resolving 24,000 noun nodes and 11,000 verb nodes. The study of semantic ambiguity in text. Words in definitions the nature of the "topmost" nodes in these hierarchies. appear in the company of their prototypical and the structure of the trees reveal information about associates. the nature of the dictionary's organization of the language, the concept of semantic primitives and other Third, dictionary data can provide the basis for aspects of lexical semantics. The data proves that the creating case gr-,-~-r descriptions of verbs, and noun dictionary offers a fundamentally consistent description argument descriptions of nouns. Semantic templates of of word meaning and may provide the basis for future meaning are far richer when one considers the research and applications in computational linguistic taxonomic inheritance of elements of the lexicon. systems. Fourth. the dictionary should offer a classification which anthropological linguists and psycholinguists can use as an objective reference in comparison with 1. INTRODUCTION other cultures or human memory observations. This isn't to say that the dictionary's classification is the same as the culture's or the human mind's, only In the late 1960"s, John 01ney et al. at System that it is an objective datum from which comparisons Development Corporation produced machine-readable copies can be made. of the Merriam-Webster New Pocke~ Dictionary and the Sevent~ Collegiate Dictionary. These Fifth. knowledge of how the dictionary is structured massive data files have been widely distributed within can be used by lexicographers to build better the computational linguistic community, yet research dictionaries. upon the basic structure of the dictionary has been exceedingly slow and difficult due to the Significant And finally, the dictionary if converted into a computer resources required to process tens of thousands computer tool can become more readily accessible to of definitions. all the disciplines seeking Co use the current paper-based versions. Education. historical The dictionary is a fascinating computational resource. linguistics, sociology. English composition, etc. can It contains spelling, pronunciation, hyphenation, all make steps foxward given that they can assume capitalization, usage notes for semantic domains, access to a dictionary is immediately available via geographic regions, and propriety; etymological, computer. I do not know what all these applications syntactic and semantic information about the most basic will be and the task at hand is simply an elucidation units of the language. Accompanying definitions are of the dictionary's structure as it currently exists. example sentences which often use words in prototypical contexts. Thus the dictionary should be able to serve as a resource for a variety of computational linguistic needs. My primary concern within the dictionary has 2. "TANGLED" HIERARCHIES OF NOVN S AND VERBS been the development of dictionary data for use in understanding systems. Thus I am concerned with what dictionary definitions tell us about the semantic and The grant. MCS77-01315, '~)evelopment of a Computational pragmatic structure of meaning. The hypothesis I am Methodology for Deriving Natural Language Semantic proposing is that definitions in the lexicon can be Structures via Analysis of Machine-Readable studied in the same manner as other large collections of Dictionaries". created a taxonomy for the nouns and objects such as plants, animals, and minerals are verbs of the Merriam-Webster Pocket Dictionary (MPD), studied. Thus I am concerned with enunerating the based upon the hand-disambiguated kernel words in their classifications1 organization of the lexicon as it has definitions. This taxonomy confirmed the anticipated been implicitly used by the dictionary's lexicographers. structure of the lexicon to be that of a "tangled hierarchy" [8,9] of unprecedented size (24,000 noun Each textual definition in the dictionary is senses. 11.000 verb senses). This data base is believed syntactically a noun or verb phrase with one or more to be the first Co be assembled which is representative kernel terms. If one identifies these kernel terms of of the structure of the entire English lexicon. (A definitions, and then proceeds to disambiguate them somewhat similar study of the Italian lexicon has been relative to the senses offered in the same dictionary done [2.11] ). The content categories agree under their respective definitions, then one can arrive substantially with the semantic structure of the lexicon at a large collection of pairs of disambiguated words proposed by Nida [I5], and the verb taxonomy confirms which can be assembled into a taxonomic semi-lattice. the primitives proposed by the San Diego LNR group [16].
This task has been accomplished for all the definition This "tangled hierarchy" may be described as a formal texts of nouns and verbs in a comu~n pocket dictionary. data structure whose bottom is a set of terminal This paper is an effort to reveal the results of a disambiguated words that are not used as kernel defining preliminary examination of the structure of these terms; these are the most specific elexents in the databases. structure. The tops of the structure are senses of words such as "cause", "thing", '*class", "being", etc. The applications of this data are still in the future. These are the most general elements in the tangled What might these applications be? hierarchy. If all the top terms are considered to be
133 members of the metaclass "
(a b c e f) a Table 2. Frequencies and Maxim,-. Depths of (a b c gk) I MPD Tangled Noun Hierarchies (a b d g k) I (a b c g I) b 3379 I00NE-2.1A 1068 13 MEASUREMENT-I.2A (a bd gl) / \ 2121 12 BULK-I.IA 1068 ** DIMENSION-.IA (abc gin) / \ 1907 10 PARTS-I.1A/! 1061 ** LENGTH-.IB (a b d g m) c d 1888 10 SECTIONS-.2A/! 1061 ** DISTANCE-I.IA (a b d i) II I \ 1887 9 DIVISION-.2A 1061 14 DIMENSIONS-.IA / J / \ 1832 9 PORTION-I.4A 1060 11 SZZE-I.0A • I / i 1832 8 PART-I.IA 1060 13 MEASURE-I.2A [ f / 1486 14 SERIES-.0A 1060 I0 EXTENT-.IA I I/ 1482 18 SUM-I.IA I060 14 CAPACITY-.2A f g 1461 ** AMOUNT-2.2A 869 7 HOUSE-I.1A/+ /I\ 1459 8 ACT-I.1B 836 7 SUBSTANCE-.2B /I\ 1414 ** TOTAL-2.0A 836 8 MATTER-I.4A / I \ 1408 15 NUMBER-I.IA 741 8 NENS-.2A/+ k 1 m 1379 14 AMOUNT-2.1A 740 6 PIECE-I.2B 1337 80NE-2.2A 740 7 ITEM-.2A 1204 5 PERSON-.IA 686 7 ELZMENTS-.IA Figure I. The Trace of a Tangled Hierarchy 1201 14 OPERATIONS-.IA/÷ 684 6 MATERIAL-2.1A 1190 ~r* PROCESS-I.4A 647 9 THING-.4A 1190 14 ACTIONS-.2A/+ 642 8 ACT-I.IA 2.1 TOPMOST SEMANTIC NODES OF THE TANGLED HIERARCHIES 1123 6 GROUP-I.OA/! 535 6 THINGS-.SA/! ii01 12 FOEM-I.13A 533 6 MEMBER-.2A 1089 12 VAEIETY-.4A 503 I0 PLANE-4.1A Turning from the abstract description of the forest of 1083 Ii MODE-.IA 495 6 STRUCTURE-.2A tangled hierarchies Co the actual data, the first 1076 I0 STATE-I.IA 494 I0 RANK-2.4A question which was answered was, 'What are the largest 1076 9 CONDITION-I.3A 493 9 STEP-I°3A tangled hierarchies in the dictionary?". The size of a tangled hierarchy is based upon two numbers, the maximum *~ = ouC of range due to dace error depth below the "root" and the total number of nodes transitively reachable from the root. Thus the tangled hierarchy of Figure 1 has a depth of 5 and conCains a Table 3. Frequencies of Topmost total of 11 nodes (including the "root" node, "a"). MPD Tangled Verb Hierarchies However, since each non-terminal in Che tangled hierarchy was also enumerated, it is also possible Co 4175 RZMAIN-. 4A 365 GAIN-2.1A describe the "sizes" of che other nodes reachable from 417 5 CONTINUE-. IA 334 DRIVE- I. IA/+ "a". Their number of elemenCs and depChs given in Table 4087 MAINTAIN- .3A 333 PUSH-I .IA 1. 4072 STAND-1.6A 328 PRESS-2 olB 4071 HAVE-1.3A 308 CHANGE- I .IA 4020 BE- .IB 289 MAKE- 1.10A Table 1. Enumeration of Tree Sizes and Depths of 3500 EQUAL-3.0A 282 COME- .IA Tangled Hierarchy Nodes of Figure 2 3498 BE- .IA 288 CHANGE-I .IA 3476 CAUSE-2.0A 283 EFFECT- 2 .IA 1316 APPEAR- .3A/C 282 ATTAIN-. 2B Tree Maximum Rooc 1285 EXIST-. IA/C 281 FORCE-2.3A Size Depth Node 1280 OCCUR- .2A/C 273 PUT- .IA 1279 MAKE-I .IA 246 IMPRESS-3.2A ii 5 a 567 GO-1 .iB 245 URGE- 1.4A 10 4 b 439 BRING- .2A 244 DRIVE-I .IA 6 3 c 401 MOVE- I .IA 244 IMPEL- .0A 6 2 d 366 GET-I .IA 244 THRUST- I .IA 4 l g 2 I e While the verb tangled hierarchy appears co have a series of nodes above CAUSE-2.0A which have large These examples are being given co demonstrate the numbers of descendants, the actual structure more inherenC consequences of dealing wich tree sizes based closely resembles chat of Figure 2.
134 TYPE 1.4A - a c~ass, k~nd, or 2rouo set apart by com~on characteristics remain-.&a <--> continue-.la <-- maintain-.3a I KIND Io2A - a 2rouv united by common traits or stand-l.6a interests KIND 1.2B - CATEGORY have-1.3a t ,CATEGORY .0A - a division used in classification ; be-.lb CATEGORY .0B - CLASS, GROUP, KIND
equal-3.0a DIVISION .2A one of the Darts, sections, or 7 =rouDinas into which a whole is divided be-.la *GROUPING <-" W7 - a set of objects combined in a cause-2.0a group t ? SET 3.5A - a zrouv of persons or things of the same 8o-l.la < > make-l.la make-l.la kind or having a common characteristic usu. classed together
Figure 2. Relations between Topmost Tangled SORT 1.1A - a 2tour of persons or things that have Verb Hierarchy Nodes similar characteristics SORT 1.1B - C~%SS
The list appears in terms of descending frequency. The SPECIES .IA - ~ORT, KInD topmost nodes don't have many descendants at one level SPECIES .IB - a taxonemic group comprising closely below, but they each have one BIG descendant, the next related organisms potentially able co breed with node in the chain. CAUSE-2.0A has approximately 240 one another direct descendants, and MAKE-I.IA has 480 direct descendants making these t~o the topmost nodes in terms of number of direct descendants, though they are Key: ranked 9th and 13th in terms of total descendants (under * The definition of an MPD run-on, taken from Webster's words such as EDL%IN-.4A, CONTINUE-.1A, etc.). This SevenE~ Colle2iate Dictionary to supplement the set. points out in practice what the abstract tree of Figure I showed as possible in theory, and explains the seeming contradiction in having a basic verb such as Figure 3. Noun Primitive Concept Definitions "CAUSE-2.0A" defined in terms of a lesser verb such as '~EMAIN-.4a". SET 3.5A The difficulty is explainable given two facts. First. t \ the lexicographers HAD to define CAUSE-2.0A using some / \ number of INDIVIDUALS other verb, etc. This is inherent in the lexicon being GROUPINGS* \ 7 used to define itself. Second, once one reaches the Cop one of the PARTS* \ / of a tengled hierarchy one cannot go any higher -- and SECTIONS* \ / consequently forcing further definitions for basic verbs l ¼ / such as "be" and "cause" invariably leads CO using more / CROUP 1.0A < ...... specific verbs, rather than more general ones. The / 7 t t % situation is neither erroneous, nor inconsistent in the DIVISION .2A / / \ \ context of a self-defined closed system and will be ? / I I \ discussed further in the section on noun primitives. / / I I \ / / CLASS KIND \ / / 1 .IA 1.2A I / I tt% t I 2.2 NOUN PRIMITIVES CATEGORY .0A CATEGORY .0S I TYPE 1.4A I % tl I I \ I I I I One phenomenon which was anticipated in computationally \ I I I I grown trees was the existence of loops. Loops are \ I I SORT I.IB I caused by having sequences of interrelated definitions KIND 1.2B I SORT 1.1A whose kernels form a ring-like array [5.20]. However. what was not anticipated was how important such clusters I\ / of nodes would be both co the underlying basis for the I / Caxonomies and as primitives of the language. Such SPECIES .IA .... SPECIES .IB circularity is sometimes evidence of a truly primitive concept, such as the set containing the words CLASS, GROUP, TYPE, KIND, SET. DIVISION, CATEGORY. SPECIES, Figure 4. "GROUP" Concept Primitive from INDIVIDUAL, GROUPING, PART and SECTION. To understand Dictionary Definitions this, consider the subset of interrelated senses these words share (Figure 3) and then the graphic * Note: SECTIONS, PARTS, and GROUPINGS have additional representation of these in Figure 4. connections not shown which lead to a related primitive cluster dealing with the PART/WHOLE concept.
GROUP 1.0A - a number of individuals related by a common factor (as physical association, This complex interrelated set of definitions comprise a community of interests, or blood) primitive concept, essentially equivalent to the notion of SET in mathematics. The primitiveness of the set is CLASS 1,1A - a KrouD of the same general status or evident when one attempts to define any one of the above nature words without using another of them in that definition.
135 This essential property, the inability to write a Table 4. 50 Most Frequent Verb Infinitive Forms of definition explaining a word's meaning without using W7 Verb Definitions (from [19]). another member of some small set of near synonymous words, is the basis for describing such a set as a PRIMITIVE. It is based upon the notion of definition 1878 MAKE 157 FURNISH given by Wilder [21], which in turn was based upon a 908 CAUSE 154 TURN presentation of the ideas of Padoa, a 815 BECOME 150 GET turn-of-the-century logician. 599 GIVE 150 TREAT 569 BE 147 SUBJECT The definitions are given, the disambiguation of their 496 MOVE 141 HOLD kernel's senses leads to a cyclic structure which cannot 485 TAKE 137 UNDERGO be resolved by attributing erroneous judgements to 444 PUT 132 CHANGE either the lexicographer or the disambiguator; therefore 366 BRING 132 USE the structure is taken as representative of an 311 HAVE 129 KEEP undefinable pyimitive concept, and the words whose 281 FoRM 127 ENGAGE definitions participate in this complex structure are 259 GO 127 PERFORM found Co be undefinable without reference to the other 240 SET 118 BREAK members of the set of undefined terms. 224 COME 118 REDUCE 221 REMOVE 112 EXPRESS The question of what to do with such primitives is not 210 ACT 107 ARRANGE really a problem, as Winograd notes [22], once one 204 UTTER 107 MARK realizes that they must exist at some level, just as 190 PASS 106 SEFARATE mathematical primitives must exist. In tree 188 PLACE 105 DRIVE construction the solution is to form a single node whose 178 COVER 104 CARRY English surface representation may be selected from any 173 CUT I01 THR02 of the words in the primitive set. There probably are 169 PROVIDE 100 SERVE connotative differences between the members of the set. 166 DRAW 100 SPEAK but the ordinary pocket dictionary does not treat these 163 STRIKE 100 WORK in its definitions with any detail. The Merriam-Webster CollemfaCe Dictionary does include so-called "synonym paragraphs" which seem to discuss the connotative This gives US four OeW terms, "structure", "SpOt", differences between words sharing a "ring". "situation", and "location". Looking these up we find the circularity forming the primitive group. While numerous studies of lexical domains such as the verbs of motion [1,12,13] and possession [10] have been structure-.2a - ~ built (as a house or a dam) carried out by ocher researchers, it is worth noting that recourse to using ordinary dictionary definitions spot-l.3a - LOCATION, SITE as a source of material has received little attention. Yet the "primitives" selected by Donald A. Norman, location-.2a - SITUATION, PLA~ David E. Romelhart, and the LNR Research Group for knowledge representation in their system bear a situatiou-.la - location, site remarkable similarity to those verbs used must often as kernels in The Merriam-Webster Pocket Dictionary and And finally, the only new term we encounter is "site" Donald Sherman has shown (Table 4) these topmost verbs which yields, to be among the most common verbs in the Collegiate Dictionary as well [19]. The most frequent verbs of the site-.Oa - location <~ of a building>
place-l.3a - a building or locality used for a Fisure 5. Diagram of Primitive Bet Containing PLACE. special purpose LOCALITY, SPOT, SITE, SITUATION, and LOCATION
The kernels of this definition are "building" and "locality". Lookiog these up in turn we have: 2.3 NOUNS TERMINATING IN RELATIONS building-.la a usu. roofed and wailed structure TO oTHER NOUNS OR VERBS (as a house) for permanent use
locality-.0a a particular ShOt, situation, or In addition to terminating in "dictionary circles" or location "loops", nouns also terminate in definitions which are actually text descriptions of case arguments of verbs or relationships to other nouns. "Vehicle" is a fine
136 example of the former, being as it were the canonical interaction of the PART-OF and ISA hierarchies. instrumental case argument of one sense of the verb Historically even Raphael [17] used a PART-OF "carry" or "transport". relationship together with the ISA hierarchy of gig's deduction system. What however is new is that I am not vehicle - a means of carrying or transporting stating "leaf" is a part of a plant because of some need something use this fact within a particular system's operation. but "discovering" this in a published reference source '~eaf" is an example of the letter, being defined as a and noting that such information results naturally from part of a plant, an effort to assemble the complete lexical structure of the dictionary. leaf - a usu. flat and green outgrowth of a plant stem that is a unit of foliage and functions esp. in photosynthesis. 2.4 PARTITIVES AND COLLECTIVES
Thus "leaf" isn't a type of anything. Even though under As mentioned in Section 2.3, the use of "outgrowth" in a strictly genus/differentia interpretation one would the definition of "leaf" causes problems in the taxonomy analyze "leaf" as being in an ISA relationship with if we treat "outgrowth" as the true genus term of that "outgrowth", "outgrowth" hasn't a suitable homogeneous definition. This word is but one ~*-mple of a broad set of members and a better interpretation for modeling range of noun terminals which may be described as this definition would be to consider the "outgrowth of" "partitives". A "partitive" may be defined as a noun phrase to signify a part/whole relationship between which serves as a general term for a PART of another "leaf" and "plant". large and often very non-homogeneous set of concepts. Additionally. at the opposite end of the partitive Hence we may consider the dictionary to have at least scale, there is the class of "collectives". Collectives two taxonomic relationships (i.e. ISA and ISPART) as are words which serve as a general term for a COLLECTION well as additional relations explaining noun terminals of other concepts. as verb arguments. One can also readily see that there will be taxonomic interactions among nodes connected The disambiguators often faced decisions as to whether across these relationship "bridges". some words were indeed the true semantic kernels of definitions, and often found additional words in the While the parts of a plant will include the "leaves", definitions which were more semantically appropriate to "stem", "roots", etc., the corresponding parts of any serve as the kernel -- albeit they did not appear TYPE of plant may have further specifications added to syntactically in the correct position. Many of these their descriptions. Thus "plant" specifies a functional terms were partitives and collectives. Figure 7 shows a form which can be further elaborated by descent down its set of partitives and collectives which were extracted ISA chain. For example, a "frond" is a type of "leaf", and classified by Gretchen Hazard and John White during the dictionary project. The terms under "group names", frond - a usu. large divided leaf (as of a fern) "whole units", and "system units" are collectives. Those under "individuators". "piece units". "space We knew from "leaf" that it was a normal outgrowth of a shapes", "existential units", "locus units", and "event "plant", but now we see that "leaf" can be specialized, units" are partitives. These terms usually appeared in provided we get confirmation from the dictionary that a the syntactic frame "An of" and this "fern" is a "plant". (Such confirmation is only needed additionally served to indicate their functional role. if we grant "leaf" more than one sense meaning, but words in the Pocket Dictionary do typically average 2-3 sense meanings). The definition of "fern" gives us the I QUANTIFIERS 3 EXISTENTIAL UNITS needed linkage, offering, I.i GROUP NAMES 3.1 VARIANT fern - any of a group of flowerless seedless vascular pair.collection.group version.form, sense green plants cluster,bunch. band (of people) 3.2 STATE Thus we have a specialized name for the "leaf" appendage state,condition of a "plant" if that plant is a "fern". This can be 1.2 INDIVIDUATORS represented as in Figure 6. member.unit,item. 4 REFERENCE UNITS article,strand, branch 4.1 LOCUS UNITS ISPART (of science, etc.) place.end,ground, leaf ------=='''''> plant point /\ /\ 2 SHAPE UNITS II II 4.2 PROCESS UNITS II II 2.1 PIECE UNITS cause,source,means. II II sample,bit,piece, way.manner ISA II II ISA tinge,tint II il 5 SYSTEM UNITS II II 2.2 WHOLE UNITS system, course,chain. II II mass,stock,body, succession.period II ISPART [[ quantity.wad frond =====~=~==="==''> fern 6 EVENT UNITS 2.3 SPACE SHAPES act,discharge, Figure 6. LEAF:PLANT::FHOND:FERN bed,layer.strip,belt, instance crest,fringe,knot. knob,tuft 7 EXCEPTIONS This conclusion that there are two major transitive growth.study taxonomies and that they are related is not of course new. Evens etal. [6,7] have dealt with the PART-OF Figure 7. Examples of Partitives and Collectives [3] relationship as second only to the ISA relationship in importance, and Fahlmen [8,9] has also discussed the
137 ACKNOWLEDGEMENTS 13. Miller. G., "English verbs of motion: A case study in semantic and lexical memory." in Codine This research on the machine-readable dictionary could Processes in Human Memory. A.W. Melton and not have been accomplished without the permission of the E. Martins, ed., Winston. Washington. D.C., 1972. G. & C. Merriam Co., the publishers of the Merriam- Webster New Pocket Dictiouar7 and the Merriam-Webster 14. Munro. Allen. '~Linguistic Theory and the LNR Seventh C911e~iate Dictionary as well as the funding Structural Representation." in Exml orations in support of the National Science Foundation. Thanks Coenition , Donald A. Norman and David E. Runelhart, should also go to Dr. John S. White. currently of ed., W. H. Freeman. San Francisco. 1975, pp. Siemens Corp., Boca Eaton, Florida; Gretchen Hazard; and 88-113. Drs. Robert F. Si,--~ns and Winfred P. Lehmann of the University of Texas at Austin. 15. Nida. Eugene A., Exnlorin2 S~autic Structures. Wilhelm Fink Verlag. Munich. 1975.
REFERENCES 15. Norman, Donald A., and David E. Rumelhart. Exnlorations in C~nition. W.H.Freeman. San Francisco, 1975. I. Abrahameon, Adele A, "Experimantal Analysis of the Semantics of Movement." in Explorations in 17. Raphael. Bertram, ~IR: A Comnuter Pro2raln for Cognition, Donald A. Norman and David E. Rumelhart. Semantic Information Retrieval, PhD dissertation. ed., W. H. Freeman, San Francisco, 1975, pp. M.I.T., i%8. 248-276. 18. Runelhart, David E. and James A. Lenin. "A Language 2. Alinei, Matin, La struttura del lessico, II Mulino, Comprehension System." in Exolor ations in Bologna. 1974. Co2nition, Donald A. Norman and David E. Rumelhart. ed., W. H. Freo--n, San Francisco. 1975, pp. 3. Amsler. Robert A. and John S. White. "Final Report 179-208. for NSF Project MCS77-01315, Development of a Computational Methodology for Deriving Natural 19. Sherman, Donald, "A Semantic Index to Verb Language Semantic Structures via Analysis of Definitions in Webster's Seventh New Colle~iate Machine-Readable Dictionaries," Tech. report. Dictionary." Research Report. Computer Archive of Linguistics Research Center, University of Texas at Language Materials, Linguistics Dept., Stanford Austin, 1979. University. 1979.
4. Amsler. Robert A., The Structure of the 20. Sparck Jones, Karen. '*Dictionary Circles," SDC Merriam-Webster Pocket D~ctionarv. PhD document TM-3304, System Development Corp., January dissertation, The University of Texas at Austin, 1%7. December 1980. 21. Wilder. Raymond L., Introduction to the Foundations 5. Calzolari. N., "An Empirical Approach to of ~, John Wiley & Sons, Inc., New York, Circularity in Dictionary Definitions," Cahiers de I%5. Lexicolo~ie, Vol. 31. No. 2, 1977. pp. 118-128. 22. Winograd, Terry, "On Primitives, prototypes, and 6. Evens, Martha and Raoul Smith. "A Lexicon for a other semantic anomalies," Proceedin2s of the Computer Quest ion-Answering System," Tech. Workshoo on Theoretical Issues in Natural Laneuaee report 77-14, lllinois Inst. of Technology, Dept. Processin2. June 10-13, 1975~ ~. ~qls., of Computer Science, 1977. Schank, Roger C., and B.L. Nash-Webber. ed., Assoc. for Comp. Ling., Arlington, 1978, pp. 25-32. 7. Evens, Martha. Bonnie Litowitz. Judith Markowitz, Raoul Smith and Oswald Werner. L~x~c~l-Semantic Relations: A__ Comp§rativ~ Su%-vqy. Linguistic Research. Carbondale, 1980.
8. Fahlman, Scott E., "Thesis progress report: A system for representing and using real-world knowledge," Al-Memo 331, M.I.T. Artificial Intelligence Lab., 1975.
9. Fahlman, Scott E., _A System for ReDresentin~ and Usin~ Rqq~-World Knowled2e. PhD dissertation, M.I.T., 1977.
10. Gentner. Dedre, "Evidence for the Psychological Reality of Semantic Components: The Verbs of Possession," in Explorations in Cognition. Donald A. Norman and David E. Rumelhart. ed., W. R. Freeman, San Francisco, 1975, pp. 211-246.
11. Lee, Charmaine, "Review of L__%a struttura del lessico by Matin Alinei." Lan2ua~e, Vol. 53, No. 2, 1977, pp. 474-477.
12. Levelt, W. J. M., R. Schreuder. and E. Hoenkamp, "Structure and Use of Verbs of Motion." in Recent Advances in the Psvcholoev of Laneua~e. Robin Campbell and Philip T. Smith. ed., Plenum Press, New York, 1976, pp. 137-161.
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