Base_JSON/prefixJ/json/J74/J74-1004.json

{
    "paper_id": "J74-1004",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T02:17:43.832227Z"
    },
    "title": "American Journal of Computational Linguistics",
    "authors": [
        {
            "first": "Heino",
            "middle": [],
            "last": "Viil",
            "suffix": "",
            "affiliation": {},
            "email": ""
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "We describe a branch of d i c t i o n a r y science, and recormend t h e term lexicometry for i t , t h a t deals w i t h the mathematical and statistical aspects of d i c t i o n a r i e s. I t i s related t o both and former de n o t incj the d e s c r i p t i o n of l e x i c a l m a t e r i a l and t h e latter i t s a n a l y s i s and study. Many problems i n computational l i n g u i s t i c s r e q u i r e the use of a stored d i c t i o n a r y easily a c c e s s i b l e t o a c o q u t w program. I n the course of an i n v e s t i g a t i o n , s u c h a d i c t i o n a r y may have to be expanded, reduced, rcanrranged, or modified in various ways o A l s o several n o n l i n g u i s t i c disciplines using t h e c m p u t e r , such as psychology, biology, m e d i c i n e , and s o c i o l o g y , o f t e n need a large d a t a base in t h e \u00a3 o m of a d i c t i o n a r y. The relevant s t r u c t u r a l properties of a d i c t i o n a r y , however, have n o t yet been s u f f i c i e n t l y and systematically i n v e s t i g a t e d. Research i n this area is needed i n order t o o p t i m i z e the construction af s t o r e d dictionaries and t o manipulate them i n e f f i c i e n t ways. 1 A c o n s i d e r a b l y extended version of t h i s p a p e r w a s sUbmitted t o t h e State University of N e w York i n Buffalo in partial s a t i s f a c t i o n of the r e q u i r e m e n t s for the dbcjree of of science of Ileino ~i i l. T h e project r c p r e s e n : .~ the continuation of an e a r l i e r work by 1Jickolas V. ~i n d f e r. Ilmy ideas and a l l t h e p r o g~m m i n g effort is due t o Iieino ~i i l. The w r i t e-u p is a o i n t e f f o r t. The work reported here w a s s u p p o r t e d by N a t i o n a l cience Foundation Grant G J-G 5 8 .",
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        "abstract": [
            {
                "text": "We describe a branch of d i c t i o n a r y science, and recormend t h e term lexicometry for i t , t h a t deals w i t h the mathematical and statistical aspects of d i c t i o n a r i e s. I t i s related t o both and former de n o t incj the d e s c r i p t i o n of l e x i c a l m a t e r i a l and t h e latter i t s a n a l y s i s and study. Many problems i n computational l i n g u i s t i c s r e q u i r e the use of a stored d i c t i o n a r y easily a c c e s s i b l e t o a c o q u t w program. I n the course of an i n v e s t i g a t i o n , s u c h a d i c t i o n a r y may have to be expanded, reduced, rcanrranged, or modified in various ways o A l s o several n o n l i n g u i s t i c disciplines using t h e c m p u t e r , such as psychology, biology, m e d i c i n e , and s o c i o l o g y , o f t e n need a large d a t a base in t h e \u00a3 o m of a d i c t i o n a r y. The relevant s t r u c t u r a l properties of a d i c t i o n a r y , however, have n o t yet been s u f f i c i e n t l y and systematically i n v e s t i g a t e d. Research i n this area is needed i n order t o o p t i m i z e the construction af s t o r e d dictionaries and t o manipulate them i n e f f i c i e n t ways. 1 A c o n s i d e r a b l y extended version of t h i s p a p e r w a s sUbmitted t o t h e State University of N e w York i n Buffalo in partial s a t i s f a c t i o n of the r e q u i r e m e n t s for the dbcjree of of science of Ileino ~i i l. T h e project r c p r e s e n : .~ the continuation of an e a r l i e r work by 1Jickolas V. ~i n d f e r. Ilmy ideas and a l l t h e p r o g~m m i n g effort is due t o Iieino ~i i l. The w r i t e-u p is a o i n t e f f o r t. The work reported here w a s s u p p o r t e d by N a t i o n a l cience Foundation Grant G J-G 5 8 .",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Abstract",
                "sec_num": null
            }
        ],
        "body_text": [
            {
                "text": "F ' i r s t , we review c r i t i c a l l y t h e problems o f meaning and i t s r e p r e s e n t a t i o n , t h e q u e s t i o n s r e l a t i n g t o l e x i c a l d e f i n i t i o n s . . Logical meaning applies to such attempts to deal with meaning as symbolic l o g i c and mathematics. The meanings with which the s i g n a l s of such systems correlate are unique outside-world referents or unique meanings w i t h i n the logical system t h a t e v e n t u a l l y have outside-world referents.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "General-sernant'4c meanings are a l s o uniqne in their reference to outside world, but the semanticists are less s t r i n g e n t i n scope than the l o g i c i a n s . Nevertheless, t h e i r scope is an i d e a l i z e d language, much more l i m i t e d than ordinary language.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "2.",
                "sec_num": null
            },
            {
                "text": "Communication-theory meaning is equivalent to t h e amount of information t h a t can be transmitted per u n i t time in a comunication . s y s t e m .",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "3.",
                "sec_num": null
            },
            {
                "text": "Lexicoqraphical meaning is t h a t of \"words, \" and the In the framework .of o u r particular topic w e shall be mainly concerned w i t h categories 4 and 7 .",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": ".",
                "sec_num": "4"
            },
            {
                "text": "(1 966 ) , u n i l i n g u a l d e f l n i n g d i c t i o n a r i e s appear t o be based on a model that assumes a d i s t i n c t i o n between meaning p r o p e r ( s i g n i f i c a t i o n , comprehension, i n t e n s i o n ) and t h e t h i n g meant by a s i g n ( d e n o t a t i o n , reference, e x t e n s i o n ) . On the basis of what is meant by a sign, Osgaod, s u c i , and Tannenbaum ( 1 95 7 ) distinguish three k i n d s of meaning.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "According t o Weinreich",
                "sec_num": null
            },
            {
                "text": "Pragmatical ( s o c i o l o g i c a l ) meaning : the r e l a t i o n of signs t o s i t u a t i o n s and behaviors.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "1.",
                "sec_num": null
            },
            {
                "text": "2 .",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "1.",
                "sec_num": null
            },
            {
                "text": "( l i n a u i s t i c ) meaning : the r e l a t i o n of s i g n s t o other signs.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "1.",
                "sec_num": null
            },
            {
                "text": "S e m a n t i c a l meaning: the r e l a t i o n of signs t o t h e i r s i g n i f i c a t e s . I t i s easy to see that these classes are i n correspondence with L o n g y e a r ' s three layers i n category 7. ",
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                "eq_spans": [],
                "section": "3.",
                "sec_num": null
            },
            {
                "text": "EQUATION",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [
                    {
                        "start": 0,
                        "end": 8,
                        "text": "EQUATION",
                        "ref_id": "EQREF",
                        "raw_str": "Mackey (19653 f i n d s structural meanings i n ( 1 ) structure words,",
                        "eq_num": "( 2 )"
                    }
                ],
                "section": "3.",
                "sec_num": null
            },
            {
                "text": "i n f l e c t i o n a l forms, and I n R u s s e l l ' s v i m (1 967) the s t r u c t u r e words, such as \" t h a n , I& \"or, \" \" h o w e~e r , \" have meaning o n l y in a suitable verbal c o n t e x t and c a n n o t s t a n d alone The derivative of a f at the p o i n t 1 is assumed to be 1 because a t e x t of l e n g t h 1 has a vocabulary consisting of one word, hence Thereforef' i s a function that decreases mnotonically from 1 to As a consequence of the above speculations, in t h e expression V = N~ k cannot be constant. In creating the data base, it was attempted to k e e p its structure simple and uniform without sacrificing its g e n e r a l validity. - ---.-------o------&lY-----.I--m---.Il-C-----.--.----- f o r m a t ) , ( 2 ) d e f i n i t i o n length ( a n i n t e g e r ) , ( 3 ) t y p e of entry ( a n i n t e g e r ) , ( 4 ) suhlist name. This somewhat unexpected, though not particularly surprising, words are r e l a t i v e l y scarce i n t h e l a s t t h i r d o f t h e d i c t i o n a r y The project h a s been informative i n another r e s p e c t , v h i c h ,is not u n i m p o r t a n t : it has g i v e n a n i n of runs) and 11 on the analjrsis. Although some d~b u q g i n q +had to be done, t h i s was g e n e r a l l y i n s i g n i f i c a n t as corn7are-l to t h e total effort, so t h a t nearly all t h e 14 h o u r s 9a.; hcer, u s~f . 1 1 1 r u n n i n g time. Lyons, J.",
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                "ref_spans": [
                    {
                        "start": 674,
                        "end": 727,
                        "text": "---.-------o------&lY-----.I--m---.Il-C-----.--.-----",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "3.",
                "sec_num": null
            },
            {
                "text": "( 1 9 6 9 ) . I n t After a word has be& processed, it is deleted from t h e",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "'s t a t i s t i c a l investigations of the dramas by",
                "sec_num": null
            },
            {
                "text": "Waiting L i s t . In the very f i r g t . run for a g i v e n -?I value, i .e. if K'7TSCT equals 1 , the r o u t i n e creates an nmnty l i s t for the so-zalled respectively., i n nsucceeding runs. If anv one of these produce. The procedure, however, will produce the numerical relationships des,ired.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "'s t a t i s t i c a l investigations of the dramas by",
                "sec_num": null
            },
            {
                "text": "The e x i s t i n g data base, together with its reduce& versions, has been stored on magnetic tape. and is ready to be used as i n p u t i n t o t h e propos~d procedure.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "'s t a t i s t i c a l investigations of the dramas by",
                "sec_num": null
            },
            {
                "text": "( c ) exemplification puts the d e f i n e d u n i t in functional combination with other u n i t s ; (d) a gloss is an explanator or descriptive comnent related t o the d i c t i o n a r y e n t r y ; it may also skate s i m i l a r i t i e s t o and d i f firences from other entries.",
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                "section": "",
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        ],
        "back_matter": [],
        "bib_entries": {},
        "ref_entries": {
            "FIGREF0": {
                "type_str": "figure",
                "text": "i n g e n e r a l . W e also d i s c u s s the concept of l e x i c a l valence and e l a b o r a t e a novel idea, coverage, which i s o f both t h e o r e t i c a l and p r a c t i c a l importance. I n t h i s context, r e l a t i o n s h i p 6 are e s t a b l i s h e d among three v a r i a b l e s : the s i z e of t h e covered set, the s i r e of t h e c o v e r i n g set, and the maximum d e f b i t i o n l e n g t h . both, t h e s i z e o f t h e c o v e r i n g s e t and the maximum d e f i n i t i o n l e n g t h should be s m a l l for economic c o n s i d e r a t i o n s . But decreasing one w i l l i n c r e a s e the other. s t i t u t e a b a s i s f o r o p t h i z i n g the s t r u c t u r e of a d i c t i o n a r y f o r s p e c i f i e d size of t h e covered s e t and a s p e c i f i e d machine. The p r e s e n t p i l o t project i n t h i s v i r g i n f i e l d has an o b j e c t i v e of v e r i f y i n g some c o n j e c t u r e s . It e s t a b l i s h e s some principles of c o n s t r u c t i n g , f o r m a t t i n g , and s t o r i n g a large d a t a base i n d i c t i o n a r y form. it develops programs f o r d i s p l a y i n g , handling, and modifying such a d a t a base. T h e paper o f f e r s an example how a c o n c e p t u a l l y continuous o p e r a t i o h on large amounts of data can be reduded ts o p e r a t i n g on a fraction of the whole d a t a base a t a time by s u c c e s s i v e s m a l l increments of time. W e f i n a l l y demonstrate t h e f e a s i b i l i t y o f solving l e x i c o m a t r i c problems on t h e computer and, a t t h e same time, show t h e c o s t involved i n doing such work i n terms o f b o t h human e f f o r t and machine time, w e d e s c r i b e t h e program t h a t accomplishes t h e above tasks, and the r e s u l t s that were obtained in using an e x i s t i n g dictionary of computer terminology of more than 1,800 entries. The effort required was considerable: 6 manmonth's, work and about 1 4 hours of CDC 6400 comphter time. Pxogramning was done in SLIP/AMPPL-11, a l i s t processing and associqtive memory p l u s parallel processing language package enbedded i n FORTRAN IV.",
                "num": null,
                "uris": null
            },
            "FIGREF1": {
                "type_str": "figure",
                "text": "On l e x i c o m e t r i c r e l a t i o n s h i p s among the s i z e of d ' e f i n i n g set. the size of the defined set and the maximum l e n g t h of definitions . . . . . . . . . . . . . . . . . . . . . . 1 . Some measures of coverage . . . . . . . . . . . . . . . . . . . . . . . . . . 2 . C o n s t r u c t i o n of the data base INTRODUCTION S i n c e t h e early days of e l e c t r o n i c computing, two kinds of a s s o c i a t i o n s have existed between computers and d i c t i o n a r i e s : the compuker is employed for constructing and analyzing a d i c t i o n a r y . The latter a c t i v i t y was given a s t r o n g impetus in the late 1950's by the formation o f t h e c e n t r e dlEtudes du Vocabulaire Francais and its p u b l i c a t i of syntax have been $uccessful in d e s c r i b i n g t h e rules of gramnatical accepeability of natural language utterances, the study of meaning, u s u a l l y c a l l e d semantics, has not yet produced a theory of the semantic structure of languages, based on observation and a n a l y s i s . It is beyond the scope a f t h i s paper to d i s c u s s , even s u p e r f i c i a l l y , the various viewpoints concerned w i t h the concept of meaning. One of us, V i i l (19741, h a s , however, compiled a reasonably exhaustive c r i t i c a l survey of the relevant l i t e r a t u r e . For the purposes of this work, it suffi-ces to present the following categories of meaning, as set out by Longyear (19.71)-; 1 .",
                "num": null,
                "uris": null
            },
            "FIGREF2": {
                "type_str": "figure",
                "text": "outside-world reference i s what w e o r d i n a r i l y c a l l meaning. 11 5. Psycholoqical meaning has so great a scope t h a t t h e par& involving o r d i n a r y language becomes nearly t r i v i a1 . It encompasses overt or covert behavior of any organism as responses to s t i m u l i . 6. Word-mind meaning h$q the scope equivalent to t h a t of ordinary language. The \"words \" here are l i n g u i s t i c structures, but the \"meanings\" are i d e a s , mental s t a t e s , and conceptual c a t e g o r i e s . T o o r d i n a r y meanings ( i n t h e l e x i c a l s e n s e ) here c o r r e s p o n d signals by which mental s t a t e s a r e a s c e r t a i n e d . 7. L i n q u i s t i c meaning refers to s i g n a l s as the p i e c e s o r o l i n g u i s t i c , p h~n o l o g i c a l , and s y n t a c t i c s i g n a l s .",
                "num": null,
                "uris": null
            },
            "FIGREF3": {
                "type_str": "figure",
                "text": "Homing o n t o o u r primary t a r g e t , w e may now restrict ourinterests somewhat f u r t h e r and c o n c e n t r a t e on t h e t w o l a s t classes of meaning, known under v a r i o u s d e s i g n a t i o n s b u t , b y t h e m a j o r i t y of writers, d i s t i n g u i s h e d as s t r u c t u r a l meaning and lexical meaning.",
                "num": null,
                "uris": null
            },
            "FIGREF4": {
                "type_str": "figure",
                "text": "(31 types of word o r d e r . Examples of structure words are articles and prepoai t i o n s , and these, he i n s i s t s , a l t h o u g h o f t e n called m e a n i n g l e s s o r empty, may have a large number of meanings. S i m i l a r l y , the i n f l e c t i o n a l forms, such as t h e g e n i t i v e case and p r e s e n t t e n s e , may have a number of meanings, and s o may some types of word order. L e x i c a l mefinings, on t h e o t h e r hand, refer t o the meanings of t h e c o n t e n t words, i n which the d i f f e r e n c e s i n meaning are most easily seen.",
                "num": null,
                "uris": null
            },
            "FIGREF5": {
                "type_str": "figure",
                "text": "The c o n t e n t words, which he c a l l s object words, such as p r o p e r names, class names of animals, names of c o l o r s , do not presuppose ~t h e r words and can be used i n i s o l a t i o n . T h e i r meaning i s l e a r n t by c o n f r o n t a t i o n with o b j e c t s that are what they mean or instances of what t h e y mean. A s soon as t h e a s s o c i a t i o n between an object word and what it means has been e s t a b l i s h e d by t h e l e a r n e r ' s h e a r i n g , i f f r e q u e n t l y pronounced i n the p r e s e n c e of t h e o b j e c t , t h e word i s u n d e r s t o o d also i n the absence of t h e o b j e c t . T h i $ e x p l a n a t i o n , of c o u r s e , excludes words that d e n o t e abstract e n t i t i e s , w h i c h a r e not o b j e c t -l i k e and u s u a l l y c a n n o t have a \" p r e s e n c e . \" I t a l s o d e n i e s t h a t every s t r u c t u r e word i n h e r e n t l y d e n o t e s one o r a f e w d e f i n i t e relationships even i n i s o l a t i o n . I f this were not s o , one could n o t u n d e r s t a n d what k i n d o f r e l a t i o n s h i p it d e s i g n a t e s i f used i n a c o n t e x t . Lyans (1 969) , q u i t e s e n s i b l y , d i s t i n g u i s h e s between three d i f f e r e n t k i n d s o f s t r u c t u r a l , o r grammatf cal meaning. 1 . The meaning of g r a m n a t i c a l items, such as p r p p o s i t i o n s and c o n j u n c t i o n s . 2. The meaning of g r a m m a t i c a l f u n c t i o n s , such as subject and o b j e c t , i . e . s y n t a c t i c a l r e l a t i o n s .",
                "num": null,
                "uris": null
            },
            "FIGREF6": {
                "type_str": "figure",
                "text": "The meaning a s s o c i a t e d w i t h n o t i o n s such a s d e c l a r a t i v e , i n t e r r o g a t i v e , i m p e r a t i v e , i. e. s y n t a c t i c a l types. Ile further r i g h t l y o b s e r v e s that grammatical items belong t o closed sets, which have a f i x e d , small membership, e.g. p e r s o n a l pronouns. L e x i c a l items, on t h e other hand belong t o open sets, which have an unrestricted, large memhership, e . g o nouns Moreover, l e x i c a l items have both l e x i c a l ( m a t e r i a l ) and gramnatical meaning whereas grammati ca1 items have o n l y grammatical meaning. In our work, t h e distinction between structure words and c o n t e n t s words is e s s e n t i a l . T h i s fact is c l e a r l~ seen in the preparation of the d i c t i o n a r y used for our experiments. of meaning is complex in itself, the difficulty i n c r e a s e s by another order of magnitude if one has to deal w i t h words of many n~eanings or different words w And t h e decision as to whether a given case represents o n e polysemous word or two (or more) homonyms is far from being w e l l d e f i n e d . The separation can be based on morphological c r i t e r i a . First of all, two graphematically i d e n t i c a l word forms w i t h different meanings are regarded a s homqraphs and separated i f they display a phonematic d i f f e r e n c e or i f they b e l o n g to different word classes. They are a l s o homographs even if they belong to the same word class but possess different i n f l e c t i o n systems. otherwise, they r e p r e s e n t the same word. More than one meaning of one word c o n s t i t u t e s a case of polysemy. I n contrast w i t h such d i v e r s i f i e d meanings of one word, we t a l k about h m , in which case two words have by chance acquired the same e x t e r n a l appearance. A d i s t i n c t i o n between t h e two can o n l y be made, if a t a l l , on the basis of t h e h i s t o r i c a l o r i g i n of the words invo lved. Direct, t r a n s f e r r e d and specialized s e n s e s of a word can be l i s t e d along ope dimension of meaning, dominant and basic senses r e p r e s e n t certain measures along a n o t h e r dimension. Another concept i s semantic d e p l e t i o n , i n which case t h e word occurs i n scores of e x p r e s s i o n s . Mere, the verbal o r s i t u a t i o n a l contextadds substantially t o the meaning of t h e word i n question. With polysemy, however, the context e l i m i n a t e s those senses of the word that do not apply and thereby disambiguates t h e polysemous word. It i s , therefore, i m p o r t a n t from t h e l e x i c o g r a p h i c a l p o i n t of view t o d i s t i n g u i s h between the degrees of interaction between the c o n t e x t and t h e meaning of i n d i v i d u a l (a) i n case o f weak i n \u00a3 l u e n c e , w e t a l k a b o u t a u t o s e m a n t i c o r semantically autonomous words ; t h e c o n t e x t d e f i n e s t h e 'meaning of synsemantic or semantically d e p l e t e d words. Needless to say t h a t the above, as innumerable other, d e c i s i o n s must o f t e n be based on subjective c r i t e r i a . F i n a l l y ,it could be noted that, i n e x c e p t i o n a l cases, even the inmediate c o n t e x t cannot r e s o l v e t e r c h a n g e a b i l i t y in all contexts, and identity in both",
                "num": null,
                "uris": null
            },
            "FIGREF7": {
                "type_str": "figure",
                "text": "c o g n i t i v e and emotive senses, of two lexical units (words, i n the s i m p l e s t case] are not possible i n g e n e r a l .The s e m a n t i c r e l a t i o n s h i r ; between synonymy is based on and measured by a l e v e l o f s i m i l a r i t y .Rather than d i s t i n g u i s h i n g between the \"meaning\" and the\"usage\" of a word, one s h o u l d assume the v i e w t h a t t h e former i s t h e sum t o t a l of t h e p o s s i b i l i t ! i e s of the l a t t e r . This i s b a s i c a l l y what j u s t i f i e s the e x i s t e n c e of any monolingual (and, p o s s i b l y , b i l i n g u a l ) d i c t i o n a r y . The entries i n the d i c t i o n a r i e s we are concerned with are both words (the i n t e r p r e t a t i o n and d e f i n i t i o n of which units are less than c l e a r -c u t ) and multi-word l e x i c a l units. The two are of the same s t a n d i n g and function, and t h e y w i l l be treated i d e n t i c a l l y . 3. D e f i n i t i o n s Definition is the most fuhdamental concept associated with d i c t i o n a r i e s . W e s h a l l be concerned with both classical A r i s t o t e l i a n definitions, based on \"class\" and \"characteristics\", and operational d e f i n i t i o n s which use sententialw g e n e r a t i v e terms. I n fact, it is o f t e n d i f f i c u l t or impossible t o separate equivalence o r paraphrase ciefinitions , on one hand, and those t h a t are process-oriented reproductions, on t h e other, In general., *he lexical meaning can be rendered by four basic instruments and t h e i r various combinations : (a) t h e lexicpgraphic d e f i n i t i o n enumerates t h e most important features of t h e lexical u n i t being defined, i n the simplest possible terms; (b) q u a l i f i e d synonyms provide a system of semantically most to say t h a t t h e semantic description of i n d i v i d u a l terms, the inventory of words i s the customary province of Lexicoqraphy whereas le&coloqy refers to the study o f t h e lexical material, of the recurrent patterns of semantic r e l a t i o n s h i p s , and of any formal devices, such as phonological and granmatical $ystems, that generate t h e latter. T o construct a d i c t i o n a r y of a given size,. one could choose the entries on the basis of t h e i r frequency of occurrence or in relying on some measure o f * u t i l i t y t h a t is vaguely t i e d to t h e semantic generality of the candidates. N o s o l u t i o n i s perfect or even uniformly useful over the whole dictionary. Even the arrangement of meanings of a given entry is moot. we talk about l o g i c a l , historical and empirical orders. (The latter starts with the comon and current usage followed by obsolete, colloquial, provincial, slang and technical meanings. ) he latter are primarily concerned with the lexical u n i t s of the language and a l l their l i n g u i s t i c properties . The former, on the other hand, give information about sane samponent of the e x t r a l i h g u i s tic world. Our work derives its data base from an encyclopedic dictionary. It ehould be noted t h a t the highly polysemous nature of the entries in a linguistic dictionary would have constituted an addi t iona 1 complication in this pilot project, which has now been avoided without affecting t h e general validity of the resu Its. We propose t o i n t r o d u c e the tern lexicometry to designate the, d i s c i p l i n e which investigates and analyzes the quantitative aspects o f dictionaries, t h e vocabulary of a language and various subsets of t h e l a t t e t . Lexicometry would count, weigh and . . measure, and express t h e results in s t a t i s t i c a l and mathmatical terms. Many such studies are widely known. Such is t h e one reported by G U~ raud ( 1 959 : The most frequent words are: As to the measure of frequency, n the f i r s t 100 words cover 608 of an averagen t e x t , X ( ? ) thousand words cover o n l y 2 . % of t h e t e x t . H o w e V e r , from an information theoretic p o i n t of view, the first 100 words comprise 30% of the information, words konvey a great deal of information. We could say that a frequent word i s most u s e f u l in the aggregate, and a rare word in a particular case.Other studies in glottochronology mhcern thanselves with the rate of change i n Language and i n basic vocabulary.Further,distribution of the frequencies of occurrence w i t h or without reference to any particular vocabulary has a l s o been studied.",
                "num": null,
                "uris": null
            },
            "FIGREF8": {
                "type_str": "figure",
                "text": "of the above kind is not j u s t an academic exercise to s a t i s f y the curiosity of a few l i n g u i s t s , but these relationships may have various practical applications.For example, M a a s (1972) asserts that the knowledge of a f u n c t i o n a l relation between the length of a t e x t and the size o f t h e vocabulary used i n it would be desirable in order t o estimate the e f f o r t needed f o r extension of a machine d i c t i o n a r y or i n comparison of vocabulary c o n t e n t s of t e x t s of d i f ferent l e n g t h s . In the latter case, one can standardize or normalize the t e x t s under i n v e s t i g a t i o n by reducing them t o a common minimal length through computational methods and then compare the resulting vocabulary volumes.",
                "num": null,
                "uris": null
            },
            "FIGREF9": {
                "type_str": "figure",
                "text": "Since the vocabulary of a language, however, is supposed to be restricted, so argues Maas, the existence of a l i m i t i n g value is to be postulated:V,= lim f (N)N+m As the derivative of f at a given value of N represents the -relative increase in V -1 it is to be s t a t e d that f' (N) approaches 0 with i n c r e a s i n g -N,",
                "num": null,
                "uris": null
            },
            "FIGREF10": {
                "type_str": "figure",
                "text": "Corneille have resulted in the relationship 1 log E = 0.0137. (log N) 1/3 ~h u s , if N I is given, k IC can be determined, and Vcan be calculated from Another noteworthy concept i s that of r e p e t i t i o n factor : which shows how of ten word has occurred",
                "num": null,
                "uris": null
            },
            "FIGREF11": {
                "type_str": "figure",
                "text": "The following relationship has been determined:l o g R = (0.179 log N + 0.026)~, which d i s p l a y s a very good agreement w i t h r e a l i t y . N O s i n g l e empirical law s e w s to exist between N and V f o r The Problem of Coverase We are now coming close to the core subject matter of t h i s paper. Mackey ( 1 9 6 5 ) s t a t e s t h a t he coverage or covering capacity of an item is the number of t h i n g s one can say w i t h it. It can be measured by the number of o t h e r items which it can d i s p l a c e . )I According to him, words can displace other words by Eour means: (1 ) inclusion, ( 2 ) extension, ( 3 ) combination, and (4! d e f i n i t i o n , 1, A word t h a t already includes the meaning o f other words can be used instead of these ( e . g . , seat includes chair Words the meanings of which are easily extended me'kaphorically can be used to eliminate others (e.g.,tributary of a river can be covered by branch or arm).--Certain simple words can displace others by combining e i t h e r together or with simple word endings (em g. , news + paper + man = j o u r n a l i s t ; hand + book = manual) . 4 . Certain words can be replaced by simple d e f i n i t i o n ( e r g . , breakfast can be d e f i n e d as morning meal; As an example of the a p p l i c a t i o n of the above principle, in the derivation of Basic English (by definition), t h e language was f i r s t reduced to 7500 words, and, by r e d e f i n i t i o n , cut down t o 1500. These were further reduced t o t h e eventual 850 by a technique of \"panoptic\" d e f i n i t i o n (eliminate each word on t h e grounds that i t i s some sort of modification of o t h e r words, e. g. a modification i n time, numbe-r, or s i z e ) . Basic English, which was founded essentially on the p r i n c i p l e of the p r i n c i p l e of frequency i n selection. For Ogden ( 1 933) , it was n o t the frequency of a word which makes i t u s e f u l , i t was i t s usefulness which makes it frequent. In the following part of this s e c t i o n , we attempt to present some of the salierit p o i n t s of Savard (1 970). The vocabulary i n d i c e s most widely known today are those o f frequency, of distribution, and of a v a i l a b i l i t y . But these are n o t s u f f i c i e n t to select words for a restricted vocabulary for the purpose of teaching a f o r e i g n language, such as Wench, to beginners. An objective c r i t e r i o n i s l e x i c a l v a l e n c e . I t would allow 1 . to obtain a n o v e l p r i n c i p l e of vocabulary s e l e c t i o n , 2 . t o assist the i n v e s t i g a t o r s i n s e t t i n g up a base vocabulary f o r French, is a problem of verbal economy. \\that he calls v a l e n c e i s t h e fundamental capability o f a word t o be substituted for another word. It is Mackey's coveraqe t h a t he renders a s valence, L i k e Mackey ( 1 9 6 5 ) , he maintains t h a t the s u b s t i t u t i o n of one word for another can he made by virtue of four criteria: a l with synonymy or l e x i c a l p a r a l l e l i s m . Synonyms are. words that have n e a r l y t h e same meaning, e . g .lieu and e n d r o i t . For Savard, the b a s i c criterion t h a t permits t o establish a series of the p o s s i b i l i t y of s u b s t i t u t i n g one term f o r another. One of the s i m p l e s t amng a l l the procedures of vocabulary enrichment consists o f j o i n i n g two words order to make compound words. The p r i n c i p l e 0-f combination appears as another phenomenon common t~ a l l langrlages.",
                "num": null,
                "uris": null
            },
            "FIGREF12": {
                "type_str": "figure",
                "text": "and so do the a d j e c t i v e s . A word is said to have more or less extension according to w h e a e r i t can \"cover\" a more or less great number of f u l l y or p~r t i a l l y d i f f e r e n t notions. Polysemy is the exact opposite of synonymy. Polysemy becomes complicated d w to the phenomenon of homonymy. Polysemy and homonymy constitute two very r i c h sources of l e x i c a l economy. semantic extension, Although the valence i t s e l f has rfever been mathematically measured and although there exisn o s c i e n t i f i c means of showing its existence, it has neverthe less, been proven that four formal proceaures of lexical economy permt to replace certain words by other words, and t h a t is what S a v~d c a l l s l e x i c a l valence. The postulated existence hypothesis of lexical valence leads t o the c a l c u l a t i o n of a global index of valence f o r e k d r y word. To evaluate t h e power of o f a word, one i n s p e c t s , in t h e dictionary, each element of the general 139t and counts how many times a word e n t e r s i n t o the definition of another. To measure the power of combination of a lexical unit, one inspects in the d i c t i o n a r y all the compound words joined by a hyphen, all the Gallicisms ( i n English, these would be Anglicisms) and, in general, a l l t h e word groups. W i t h a view of a p p r a i s i n g the power of i n c l u s i o n , one inspects me units of the general l i s t in two synonym dictionaries and takes the h i g h e r number. The numbei of synonyms t h a t possess a word c o n s t i t u t e s a measure of the nunber of words f o r which can substituted. To measure the power of s e m a n t i d e x t e n s i o n , one i n s p e c t s each of t h e elements of the general list i n the d i c t i o n a r y and c o u n t s the number of meanings g i v e n by the author t o such a word in t h e list. T h e number of meanings of a word is c o n s i d e r e d as a m a s u r e of i t s power of s e m a n t i c extension. The global i n d e x of lexical valence is t h e sum of t h e four n o r m a l i z e d c o u n t s . The two c r i t e d i a h a v i n g t h e h i g h e s t c o r r e l a t i o n are d e f i n i t i o n and c o m b i n a t i o n . In the beginning of t h e study, it was assumed t h a t thk four v a r i a b l e s were entirely i n d e p e n d e n t of each o t h e r . The results of a f a c t o~a n a l y s i s i n d i c a t e that they are n o t c o m p l e t e l y so. A factor r o t a t i o n shows, however , that t h e variables are s u f f i c i e n t l y i n d e p e n d e n t t o make it necessary t o retain the four c r i t e r i a of l e x i c a l valence. A comparison of t h e rank of t h e first 40 c o n t e n t words on the valence scale w i t h the same words on t h e f r e q u e n c y l i s t allows t o frame a hypothesis t h a t t h e c o r r e l a t i o n between v a l e n c e and f r e q u e n c y would be rather weak. A more c o m p l e t e study would show w i t h o u t doubt that: w e have there two very different s e l e c t i o n p r h c i p l e s . I n c o n c l u s i o n , i eSan be stated with c o n f i d e n c e that t h e measure of valence i s n o less v a l i d t h a n that of frequency, distribution . and a v a i l a b i l i t y . These c o n c e p t s w i l l eventually lead to more efficient d i c t i o n a r i e s with respect to precision, compactness and l e x i c a l economy. ON LEXICOMETRIC RELATIONSHIPS AMONG THE SIZE OF DEFINING SET, TUE: SIZE OF DEFINED SET AND TILE MAXIMUM LENGTH OF DEFINITIONS 1. Some Measures of Coverage A d i c t i o n a r y may be considered efficient and economical i f i t u s e s a reasonably small set of words to d e f i n e 9 r e l a t i v e l y large set o f entries. W e have, however, a very vague idea a b o u t what size v o c a b u l a r y is needed t o c o v e r a g i v e n number of d i c t i o n a r y e n t r i e s . (The related problem of c i~c u l a r d e f i n i t i o n s seems t o have t o wait for a camputer s o l u t i~n . ) I t i s known, for example, that Basic E n g l i s h , Ogden (1 933) , involves a l i s t of 850 English words and 50 i n t e r n a t i o n a l words, which were e v e n t u a l l y used t o d e f i n e the 20,000 English words of Basic Ynglish D i c t i o n a r y . This gives a r a t i o of the number of covering. words to that of d e f i n e d words of 0.045. West s t u d i e d the problem of what c o n s t i t u t e s a simple definition and e s t a b l i s h e d a minimum defining vocabulary of 1 , 4 90 words. The meaning of sane 18,000 words and 6,OQ'u idioms, i.e. about 2 4 , 0 0 0 expressions, was e x p l a i n e d exclusively by t h e s e 1,490 words, which were not d e f i n e d themselves. The results were published in 1961 as The 14ew Method English D i c t i o n a r y bf H o p m West and J. G. E n d i c o t t . The c o r r e s p o n d i n g size r a t i o here i s 0.062, The above r o u g h l y i n d i c a t e s that a set of about 1.0 00 words can define d s e t of about 20 times mat s i z e , but in g e n e r a l the behavior of these variables h a s not been i n v e s t i g a t e d and i s not known i n any d e t a i l . One of us, in F i n d l e r ( 1 3 7 0 ) , has formulated t h e problem i n de.Ein ; ie terms, Three v a r i a b l e s were considered : ( 1 ) t h e covered set S of size % , (2) the Coverinq set R o f s i z e % , and L the'max&mum definition\\ l e n g t h -N, such t h a t each word in S can -1 bq d e f i n e d by at m o s t N ordered words -The t a s k f i n d : ( a ) VR a s a function of vS at different v a l u e s of -N as a parameter, and (b) v as a f u n c t i o n of N at d i f f e r e n t values of v -Usinq the terminology of increment ratio for Av /Av and s i z e =; : S r a t i o f o r vR/vS , it was p o s t u l a t e d f o r case (a) that 2 * t h e increment r a t i o is, i n q e n e r a l , less than one , 2 * t h e i n c r e m e n t ratio, i n g e n e r a l , decreases as v i n c r e a s e s , S -* f o r l a r g e values of P, vR L a s y m p t o t i c a l l v approaches a l i m i t i n g value as vS increases, -* t h e increment ratio will, n e v e r exceed the s i x e ratio. L A n e x c e p t i o n t o t h i s rule would occur i n a d i c t i o n a r y s y s t e m , which does n o t treat liomon~ms as i n d i v i d u a l entries, A every time a new word with many homonyms i s introduced into the Covered Set.",
                "num": null,
                "uris": null
            },
            "FIGREF13": {
                "type_str": "figure",
                "text": "was f u r t h e r asSumed t h a t f o r B=l , the coverincr set and the covered set are of the. same s i z e , i .o. both the increment ratio and the s i z e ratio equal one. We 'must now correct this s t a t e m e n t becallse not every word i s d e f i n e d by i t s e l f o n l y . If a new word is Lntroduced that already has a synonym in the covering s e t , i t w i l l be d e f i n e d by that synonym. Then the inc'rement ratio i s 0 and t h e s i z e r a t i o become less t h a n 1.For tke second c a s e , (b) , it is n o s t u l a t e d t h a t* v monotonically decreases as I) N increases, * f o r any fixed v v a l u e , vasymptotically approaches a m i t qs 11 increases w i t h o u t bbund. C I t was finally p o i n t e d o u t t h a t vR s h o u l d be small. ko minimize s t o r a g e requirements,, and -N should he small t o mlnlmize processing t i m e and output volume. A . compromise on these mnf l i c t i n g requirements is needed. The u l t i m a t e q u e s t i o n i s :g i v e n \"What are t h e optimum yl and -11 values for a v f o r certain -A s computer a p p l i c a t i o n s on a machine with a given c o s t s t r u c t u r e ? \" X t i s reasooable to assume that the behavior of the three v a r i a l e s and t h e r e f o r e the answer to the l a s t q u e s t i o n w i l l l a r q e l y denend on t h e semaptic index of t h e elements of the covered set: and on the lexical v a l e n c e of t h e elements of the coverins s e t , The l a t t e r i m p l i e s that, f o r A n efficient and economical di,ktionary, the emmknts of t h e c o v e r i n g set must be chosen fro* t h e available vocabulary on the h a s i s of a c a r e f u l analysis. As research aimed at these goals is pratically nonexistent, it is safe to assume t h a t most of t h e existing dictionaries are s u b o p t i m a l . Work i n this area will be u s e f u l , c h a l l e n g i n g , and rewarding, b u t the investigators must be prepared to spend a considerable amount of time and effort on it. So much the more as the entire problem complex o u t l i n e d i n tFle preceding parts w i l l directly or i n d i r e c t l y enter i n t o such investigations. ThR project described here is only a small b e g i n n i n g . I t v a s o r i g i n a l l y intended t o complete the investigation of both cases, (a) and (b) , defined above. In view of the effort needed, i n terms of human and machine time, only t h e f i r s t part i-s accomplished at the time of writing this report. Appendix. I1 contains the design of the program f o r case (b) .2 . C o n s t r u c t i o n of the Data BaseThe data base was n o t derived from a text but was based on an existing d i c t i o n a r y of computer terminology,Chandor ( 1 9 7 0 ). A derivation from a text, if used, should be automatic and woulcl constitute a large-scale programming project in i t s own rigslt:",
                "num": null,
                "uris": null
            },
            "FIGREF14": {
                "type_str": "figure",
                "text": "t r i e d t o avoid problems that would introduce d i s t r a c t i n g complications, from both theoretical and practical noint of view, into the subsgquent operations. All t h i s led to t h e selection -30and construction p r i n c i p l e s outlined below. T e r m s w i t h excessively long definitions were avoided, i.e. d e f i n i t i o n s were held r e a s o n a b l y s h o r t . It was found that lexical units limiting bhe maximum d e f i n i t i o n l e n g t h to 22,,did not u n d u l v d r e s t x i c t t h e selection. I n some cases too long d e f i n i t i o n s were shortened by leaving out redundant words, g l o l s e s , r nxplanatorv notes. Every element of the c o v e r e d set was considered a l e x i c a l item, regardless of whether t h e oriqinal d i c t i o n a r y entry consisted o fa one, two, or more vrords. For p r o g r a m i n g convenience every word was coded as a s t r i n g of no more t h a n computer a s ABSIrALCOnIP. Polvsemous terms were avoided. 1f such a term was u s e d , o n l v i t s d o m i n a n t meaning was recorded. In the d a t a -b a s e d i c t i o n a r y , t h e n , each entry (element of t h r covered set) has only o n e meaning and one definition. T e f m s used in the definitions (elements of theacopering set) were a l s o c o n s i d e r e d t% be l e x i c a l items, i.e. oriqi nal multiword terms appear as a s i n g l e element, and every element is represented as a s t r i n g of no more than 1 q symbols. All terms o c c u r r i n g in t h e d e f i n i t i o n s are themselves d e f i n e d , i.e. each element of th,e covering set appears a l s o in t h e covered set. This p r i n c i p l e implies t\\at there i s a S e t of words each e l e m e n t of w h i c h i s d e f i n e d by itself. Such a sat may be called the basic v o c a b u l a r y , consisting of vrords the meanings o f which t h e user of the d i c t i o n a r y i s suprmsed t o know i n o r d e r t o use t h e d i c t i~n a~z y . As in this particular case, the d i c t i o n a r y is one of computer terms and t h e hasic voca5nlary contains t h e n o n t e c h n i c a l words u s e d in the d e f i n i t i o n s of the t e c h n i c a l terms. I n t h e d e f i n i t ' i o n s , a d e f i n i t e d i s t i n c t i o n was made Sctween c o n t e n t words and f u n c t i o n words, also c a l l e d o p e r a t o r s . The latter were n o t included i n t h e covering s e t nor were t h e y counted i n d e t e r m i n i n g the definition length. Hence, thcs c o v e r i n g set ~o n s i s t s o n l y of c o n t e n t words. The set of f u n c t i o n words i s d e f i n e d rather broadly. I't contains a wide v a r i e t y of expressions that do not d i r e c t l y contribute a n y t h i n g t o t h e c o n t e n t of t h e d e f i n i t i o n h u t o n l y i n d i c a t e grammatical and l o g i c a l rel.ationships between t h e worgs t h a t form the c o n t e n t . I t includ'es: 1 ) p r e p o s i t i o n s , e . g . o f , i n t o ; f . -2 ) c o n j u n c t i o n s , e . g .and, orif; 3 ) t h e r e l a t i v e pronoun which; -4 ) combinations of preposition and r e l a t i v e pronoun, e. g o in which, t o which, by which; 5 ) p r e s e n t p a r t i c i p l e s e q u i v a l e n t t o a p r e p o s i t i o n , e . g . U L I , c o n t a i n i n g , r e p r e s e n t i n s ; c o m b i n a t i o n s p a r t i c i p l e and p r e p o s i t i o n , c o n s i s t i n g o f , oppo --sed t o , a p p l i e d to; 7 ) corhbinations of a d j e c t i v e and p r e w s i t i o n , e.g. c a p a b l e o f , e x c l u s i v e o f , equal' to; o m h i n a e i o n s of noun and p r e p o s i t i o n , e . g. part of, set o m b i n a t i o n s of p r e p o s i t i o n , poun, and p r e p o s i t i o n , e . g . i n t e r m s o f , by means of, in the form of; -p r e p o s i t i o n a l p h r a s e s associated w i t hfol lowing i n f i n i t i v e , e , g . u s e d t o , necessary to, in order -to: 1 1 ) o t h e r f r e q u e n f l y u s e d p u r e l y f u n c t i o n a l e x p r e s s i o n s , e . g. f o r example, namely, kno,wn as. A c t u a l l y , t h e f u n c t i o n words were r e p l -a c e d by code numbers i n t h e d i c t i o n a r y . The code numbers were a s s i g n e d c o n s e c u t i v e l y a!; the f u n c t i o n words were neeeed d u r i n g the c o n s t r u c t i o n of t h e d a t a base so t h a t t h e o r d e r i s p u r e l y random. A complete list o f t h e 121 f u n c t i o n words used, t o g e t h e r w i t h t h e i r code numbers, i s g i v e n i n T a b l e I.",
                "num": null,
                "uris": null
            },
            "FIGREF15": {
                "type_str": "figure",
                "text": "definitions were somewhat s i m p l i f i e d and standardized. I n t h i s p r o c e s s , a r t i c l e s were omitted (many l a n g u a g e s do very well without them).. On the o t h e r hand, implicit r e l a t i o n s h i p s were made e x p l i c i t . A f e w examples shall serve as i l l u s t r a t f i o n s , with the f u n c t i o n words ( i n parentheses) i n s e r t e d e x p l i c i t l y i n s t e a d of t h e i r code numbers. Original dictionary entry: a b e r r a t i o n A defect i n t h e e l e c t r o n i c lens svstem of a c a t h o d e ray tube. D e f i n i t i o n i n t h e d a t a base: DEFECT ( i n ) SYSTEM (of) ELECTRO?JIC LENS (of) system) means \"system of e l e c t r o n i c le-n?ns\" (as opposed t o \" e l e c t r o n i c system of l e n s \" ) , and this r e l a t i o n s h i p i s made e x p l i c i t . Yote a l s o t h a t \"cathode r a y tuben i s a single lexical item, Nouns are represented i n s i n g u l a r , thus avoiding anothcr dictianary entry for plural or, what would he worse, p r o q r a m i n q a \"grammar.\" Likewise, f i n i t e v e r b forms are r e p r e s e n t e d i n t h i r d p e r s o n p l u r a l present indicative active, Avoiding the third person s i n g u l a r ~M m i n a t e s another d i c t i o n a r y e n t r v , and a v o i d i n q t h e passive voice eliminates a great *any participles, which otherwise would have had to he e n t e r e d . Of course, present and p a s t p a r t i c i p l e s ( t h e former i d e n t i c a l t o gerund i n form) c o u l d n o t always be avoided and had t o be e n t e r e d i n t h e d i c t i o n a r y where needed. A u x i l i a r y verbs were a u t o m a t i c a l l y eliminated by a v o i d i n g compound t e n s e s and t h e passive voice. F i n a l l y , \"to d o n a s s o c i a t e d 7~3th negation was s i m p l y omitted. O r i g i n a l : a b s o l u t e coding Program i n s t r u c t i o n s which have been w r i t t e n i n a b s o l u t e code, and do not r e q u i r e further p r o c e s s i n g before being i n t e l l i g i b l e to t h e computer. Data-base e n t r y : ABSOCODING D e f i n i t i o n : PROGRAM INSTRUCT10 (which) ONE WRITE ( i n ) ABSOLUCODE (and whic5 not) REQUIRE FURTHER PROCESSING ( b e f o r e ) INTELIGIBL ( t o ) COMPUTER Note that t h e f i r s t predicate i n the r e l a t i v e c l a u s e , third person p l u r a l perfect i n d i c a t i v e passive, i s represented by t h e s i n g n l a r i n d e f i n i t e pronoun \"one\" as subject, f o l l o w e d by t h e s t a n d a r d p l u r a l a c t i v e verb. The a u x i l i a r y \"do\" has been o m i t t e d and t h e n e g a t i o n i s r e p r e s e n t e d by a f u n c t i o n word. The v i r t u a l l y redundant \"being\" has also been l e f t o u t . I n general, the copula is o m i t t e d (some l a n g u a g e s do very w e l l without i t ) . O r i g i n a l : analytical f u n c t i o n g e n e r a t o r A f u n c t i o n generator i n which t h e F u n c t i o n i s a physical law. A l s o lcnown as naturAl laiu f u n c t i o n -3 8g e n e r a t o r , n a t u r a l f u n c t i p n g e n e r a t o r . Data-base e n t r y : AI\\ILYTI;T\\TC,EN l3efinitio.n : FUWCGENRTR ( i n which) T'Il~TCTIOtJ PM'ISICAL LAW IJote a l s o the omission of t h e g l o s s \"Also known as The stylized definitions are easily understandable even to human readers as t h e p r i n t o u t of t h e dictionary d e m o n s t~a t e s . The d a t a base was c o n s t r u c t e d by selecting the first e n t r y , then e n t e r i n g all the l e x i c a s e q u e n t l v A entering all the l e x i c a l items in the d e f i n i t i o n s of these etc. Words t h a t were n o t defined in t h e original d i c t i o n a r y were entered and defined by t h e m s e l v e s ; they c o n s t i t u t e t h e basic vocabulary. -T h i s procedure was continued u n t i l e v e r y t h i n g was d e f i n e d , i.e, u n t i l all t h e terms i n t h e c o v e r i n g s e t were also i n t h e c o v e r e d set. Then t h e n e x t e n t r y was selected from the dictionary, and t h e above process was repeated. It had been tentatively intended to compile a covered set of a b o u t 1 , 0 0 0 lexical items. When this number was reached, a rough pencil-and-paper check indicated that the size ratio was a b o u t 0.91 a t that point. It was then decided that the d a t a base sould he somewhat l a r g e r to show the relationships under investigation more p e r c e p t i b l y , and more words were added. \\fien the size r a t i o had d e c r e a s e d to about 3.79, the c o n s t r u c t i o n of. t h e d a t a base was concluded a s p r o c & s s i n g difficulties were anticipated with t o o l a r g e a d a t a volume. A t that point the data-base dictionary had p r e c i s e l y 1 , 8 5 6 e n t r i e s (as was later verified by the program). T h i s was c o n s i d e r e d t o be a s a t i s f a c t o r y compromise. T h e d i c t i o n q r y was arranged i n the form of a SLIP l i s t , P i n d l e r e t a l . ( 1 3 7 1 ) . Everve n t r y (element of t h e covered s e t ) o c c u p i e s four c e l l s i n this l i s t :( 1 ) e n t r y word ( i n A 1 0",
                "num": null,
                "uris": null
            },
            "FIGREF16": {
                "type_str": "figure",
                "text": "h r e e t y p e s of e n t r i e s t were d i s t i n g u i s h e d for programming convenience : 1)code 0 indicates t h a t t h e e n t r y i t s e l f i s not used i n .any d e f i n i t i o n , i.e. it o c c u r s only in t h e covered set and n o t in the covering s e t ; 2 code 1 i n d i c a t e s that the entry occurs i n b o t h sets and i s n o t a n element o f t h e h a s i c v o c a h u l a r y ; 3 code 2 i n d i c a t e s that the entrs i s d e f i n e d by i t s e l f , i.e.i t belongs t o t h e b a s i c vocabularv. -The s u b l i s t , t h e name of which i s i n t h e f o u r t h c e l l f o r every entry i n t h e main l i s t , contains t h e d e f i n i t i o n . This arrangement conveqiently separates the e n t r y words from those I n t h e d e f i n i t i o n s . A c e l l i n this second l e v e l c o n t a i n s either a word (in A l r ) format), i . e . an element of t h e covering set, o r a sublist name. The codes for f u n c t i o n words (integers) are c o n t a i n e d i n the c e l l s i n t h e t h i r d l e v e l . T h i s arrangement i s convenient f o r bypassing t h e f u n c t i o n words i n p r o c e s s i n g when t h e y are not needed. A t y p i c a l d i c t i o n a r ve n t r y i s illustrated in F i g u r e 1 . I --~~--, -. -,~~-~o -. I I -L -~-------. I ) -----. ---. -----~----------. --~--. -INSERT F I G U R E 1 ABOUT E1CW The fact t h a t every d i c t i o n a r y entry owns a s u b l i s t i s p r a c t i c a l i n a n o t h e r r e s p e c t : u s e f u l information about t h e e n t r y can be c o l l e c t e d and deposited i n a d e s c r i p t i o n list associated with t h e s u b l i s t . For example, if it were d e s i r e d t o e v a l u a t e t h e definition component of t h e l e x i c a & valence of each l e x i c a l item, a prbgram could e developed t h a t c o u n t s how many t i m e s a particular i t e m occurs in the definition of o t h e r items and s t o r e s this information i n t h e d e s c r i p t i o n list c r e a t e d for t h a t i t e m . I n v e s t i g a t i o n s of this n a t u r e w i l l he done a t a-f u t u r e date. The program developed for processing a l l t h e necessary i n f o r m a t i o n is r a t h e r complex. S i n c e many of i k s o r g a n i z a t i o n a l c h a r a c t e r i s t i c s may h e of f a i r l y general interest t o those who w i s h t o engage i n l e x i c o m e t r i c s t u d i e s , a b r i e f d e s c r i p t i o n is P$g, 1.-A r e p r e s e r l t a t i v e entry In the d a t n -b a s e The r e l a t i o n s h i p s between the size of t h e c o v e r i n g set vR and t h a t of the covered set vS are summarized in T a b l e 11. The table I I l i s t s t h e size of both s e t s , the size ratio, the increment of either s e t , and t h e i n c r e m e n t r a t i o for Wur values of N.",
                "num": null,
                "uris": null
            },
            "FIGREF17": {
                "type_str": "figure",
                "text": "presents v~ as a function o f v~, with N as. a parameter, in P J D FIGURE 2 ABOUT HERE The t a b l e shows t h a t , iq general, t h e increment ratio i s less t h a n T , except for one c a s e , to w h i c h w e s h a l l r e t u r n helow.I n the meantime note that, for f u l l , d i c t i o n a r y , the t a b l e definitely v e r i f i e s t h e assumption t h a t t h e increment ratio decreases with increasing vS. This, however, does not seem to he true for t h e reduced d i c t i o n a r y . I n f a c t , for all three cases of 4 the l a t t e r , t h e ratio tends to increase w i t h i n c r e a s i n g vs.Therefore t h e single o c c u r r e n c e of t h e value 1 is p l a i n l y a random event as the r a t i o is very close t o 1 a t t h e largest as value also i n t h e two o t h e r cases.. The sequence of value3 is e v i d e n t l y approaching u n i t y .",
                "num": null,
                "uris": null
            },
            "FIGREF18": {
                "type_str": "figure",
                "text": "i n a r y -l a n g u a g e , words are n o t defined.However, a sizeable s e t of n o n t e c h n i c a l words i s n e c e s s a r y t o define t h e technical terms. A l l t h e former, i n o u r case, belong to the set of basic v o c a b u l a r y and are d e f i n e d by themselves. The r e s u l t i s a n i n o r d i n a t e p r o p o r t i o n of t h e set of basic words even i n t h e f u l l dictionary. A rough p e n c i l check d u r i n g t h e c o n s t r u c t i o n of the d a t a base shoved t h a t t h e basic v o~a h u l a r y forms a b o u t 0 . 5 5 of t h e e n t i r e covered s e t , W e r e c a l l t h a t , i n a n t i c i p a t i o n of this kind of difficulty, t h e f u n c t i o n words were eliminated from the covering s e t , t o begin w i t h . I f this had n o t b e e n done, t h e s i t u a t i o n would have been aggravated by an order of magnitude. To e l i m i n a t e , o r a t least to alleviate t h i s b i a s , a ' E o n s i d e r a h l y larger data base s h o u l d be used, which, as explained before, would have heen beyond t h e scowof this p i l o t project. Another, and more important, factor t h a t c o n t r i b u t e s t o t h e problem in q u e s t i o n is the fact t h a t o u r data-hase d i c t i o n a r y was n o t derived from a t e x t h u t c o n s t r u c t e d from another d i c t i o n a r y .This was done, as described e a r l i e r , by selecting entries s t a r t i n g from t h e beginning of t h e dictionary and stopping when the data base was of satisfactory size.A s a r e s u l t , w h i l e t h e b a s i c vocabulary may be assumed to be uniformly distributed over t h e d i c t i o n a r y , the important c o n t e n t words, w i t h lonqer d e f i n i t i o n s , are n o t . The s e l e c t i o n of e n t r i e s , i n fact, was stopped a t t h e l e t t e r H. Words beyond t h a t p o i n t are t h e r e only because t h e y happened t o o c c u r i n definitions. T h u s , at least t h e words t h a t o c c u r o n l y i n t h e covered s e t (and n o t i n t h e c o v e r i n g set) a r e crowded toward t h e b e g i n n i n g of t h e d i c t i o n a r y . What happened when t h e d i c t i o n a r y was reduced i s now o b v i o u s . The weighty words w i t h long d e f i n i t i o n s were e l i m i n a t e d h u t t h e entire basic v o c a b u l a r y remained. This, of course, is q u i t e appropriate and consistent w i t h our p r i n c i p l e s . I f , f o r example, the d i c t i a n a r y had been reduced t o N = 1 , v i r t u a l l y o n l y the b a s i c vocabulary would have been retained, and we s h o u l d have obtained tho postulated linear one-to-one r e l a t i o n s h i p between vF h i s p r o c e d u r e enhances t h e p r o p o r t i o n of t h e b a s i c vocabulary, and t h e bias i n c r e a s e s . As the t e c h n i c a l",
                "num": null,
                "uris": null
            },
            "FIGREF19": {
                "type_str": "figure",
                "text": "t o begin w i t h , the s i t u a t i o n g e t s worse, with the r e d u c t i o n , toward t h e end of t h e dictionary.T h i s accounts for t h 5i n c r e a s i n g increment ratio.The last i n c r e m e n t w i t h ?J = 1 6 must have consisted entirely of basic words, t h e r e f o r e the r a t i o of u n i t y .It is suggested t h a t , for further i n v e s t i q a t i o n , a morecomplicated d i c t i o n a r y -r e d u c t i o n program be. developed, vh-ich would comnare a l l the basic words w i t h a l l t h e r e m a i n i n g d e f i n i t i o n s and e l i m i n a t e those that do not o c c u r in any definition. Thus a b a s i c wosd would occur i n t h e dictionary o n l vi f it i s needed.in a d e f i n i t i o n , which was t h e case i n the unreduced d i c t i o n a r y This :?av .I a more n a t u r a l p r o p o r t i o r . hctveen khe basic words and others would h e restored, I t i s t h e same s e t of c i r c u m s t a n c e s t h a t a l s o e x p l a i n s t h e f a c t t h a t , i n t h e reduced d i c t i o n a r y , -. t h e i n c r e m e n t r a t i o almost c o n s i s t e n t l y exceeds t h e s i z e r a t i o . T h i s , however, i s n o t t h e case for the full dictionary, which d e f i n i t e l y v e r i f i e s t h e r e s p e c t i v e assumption i n F i n d l e r ( 1 9 7 q ) . To d e m o n s t r a t e t h a t v approaches a n upper l i m i t w i t 1 1 R i n c r e a s i n g vS f o r large N,a much larger d i c t i o n a r y v o u l d be needed, Ilovever, the curve in F i g u r e .~Z for ?1 = 2 2 unmistaIra52y shows a tendency i n t h i s d i r e c t i o n . There is, o f course, a n o t h e r way of varying N:instead .of r e d u c i n g i t , it could h e i n c r e a s e d , and c e r t a i n words i n t h e d e f i n i t i o n s could be r e p l a c e d hy t h e i r d e f i n i t i o n s . T h i s would be a complicated p r o c e d u r e and difficult t o c o n t r o l . I f few s u c h xeplacements are made, v will not change appreciably. If many R are made, some replacements tend to reintroduce precilsely t h e words o t h e r s try to eliminate. In any case, the r e s u l t would h e a set of awkward and unnatural definitions of erratic lengfhs. In order t o use such a procedure, an efficient dicFlonarp should f i r s t be compiled, with short definitions and well controlled covering set. The concept of l e x i c a l valence should he u t i l i z e d , but this entails more research in t h i s area. It ~v o u l d also gat the researcher involved in the problem discussed in t h e p r e c e d i n g parts. The curves f o r N = 16, N = 8, and N = 4 in F i g u r e 2 a1.l d i s p l a y t h e basic-vocabulary bias of the reduced d i c t i o n a r y . The l a s t one very nearly approximates a one-to-one ratio. e must appreciate the fact that the 1,047 entries of the respective reduced dictionary c o n t a i n about 1,000 5asic words. It is a l s o to he n o t e d that the full dictionary, w i t h 1\\1 = 22, in the region of v = 600 requires a l a r g e r covering set t5an any S of t h e reduced v e r s i o n s . T h i s i s understandable as we r e l l i z e that the routine that computes the data points actually simulates, r a t h e r artificially, the c o n s t r u c t i o n of a d i c t i o n a r y from a source t e x t . The full dictionarv at that stage i s close t o encompassing t h e whole source, where complex t e c h n i c a l terms are being d e f i n e d , whereas the reduced versions, at t same W l u e , are already in t h e area in which t h e b a s i c yocabulary dominates-",
                "num": null,
                "uris": null
            },
            "FIGREF20": {
                "type_str": "figure",
                "text": "d i c a t i o n of t'lc e f f o r t involved in this t y p e of work. It h~s t a k e n , 3 t o t a l of about 711 program and 013taining t h e p r i n t o u t 1 5 i 3 a matter of a b o u t 7 m i n u t e s and is t h e r e f o r e neqlisihle. Of t h e .I11 h o u r s , a h o u t 3 were spent on d i c t i o n a r v r e d u c t i o n ( t h r~c seri9s",
                "num": null,
                "uris": null
            },
            "FIGREF21": {
                "type_str": "figure",
                "text": "t i s a l s o interesting t h a t time wems t o 11e v e r y d c p e n l e n t on t h e volume of d a t a Reing + a n d l e d . 13f the 11 h o u r s , more t h n 9 were s p e n t on r u n n i n g the f u l l d i c t i o n a r y (N = 3 2 ) and aborlt 1 h o u r on t h e reduced version of .J = 1G. Completinq the r u n n i n g of the last two series (I1 = R ancl :I = 4 ) tool togetFlrr l e s s t11an an h o u r of machine time. In terms of human effort, t h e accomplis'ling of t h 4 qroject r e q u i r e d ahout six man-months' .#.or!:. F i n a l l y , Appendix I1 contains a b r i e f (.lescri?tion of 2 plannned program t h a t v~ould investiqate t h e r e l a t i o n s h i p + ? t \\ t~m n t h e s i z e of tk covering s e t an? t h e maximum d e f i n i t i o n l e n g t l l f o r fixed values of the covered set size.",
                "num": null,
                "uris": null
            },
            "FIGREF22": {
                "type_str": "figure",
                "text": "h t o express our g r a t i t u d e t o t h e manaqement of Penuuin Rooks Ltd. f o r the permission to use t h e i r puSl i c a t i n n A ~ictionarv of Computers hy A. Chandor as source f o r gexerating t h e d a t a base of t h i s oroject. ~i c t i o n a r v of Computers, P e n g u i n Books, Ilarmonds~lrorth, England. Findler , N . V . ( 1 9 7 0 ) , Some c o n j e c t u r e s i n Computational F i n d l e r , N,V., Four High Level Extensions of FORTRAN IV: SLIP, AVP?L-If, TRCETRAW and SY?IT30LANG, S3artan -Rooks, New York. Guiraud, P. (1 959), Prohlemes et mothodes Ae l a statistique l i n g u i s t i q u e , R e i d e l , Dordrecht. Longyear, L i n g u i s t i c a l l v d e t e r m i n e d categories meanings, danua Linguarum, series practica,",
                "num": null,
                "uris": null
            },
            "FIGREF23": {
                "type_str": "figure",
                "text": "r o d u c t i o n to Theoretical Linguistics, t s c h r i f t f u r M t e r d t u r w i s s e n s c h a f t und L i n g u i s t i k , -2 , N o . 8 , Hackey , CJ.F, ( 1 9 6 5) , Language Teaching A n a l y s i s , Indiana U n i v e r s i t y Press, Bloomington. P l u l l e r , C. ( 1 9 6 4 ) , Essai de s t a t i s t i q u e l e x i c a l e , , Basic E n g l i s h : An Introduction with Rules and Grammar, 4th ed., Kegan P a u l , T r e n c h , T r u h n e r & Co.i and P.H. Tannenhaum ( 1 9 57) , The Measurement of Meaning, U n i v e r s i t y of I l l i n o i s P r e s s , Urhana, I l l i n o i s , R u s s e l , B . (1967) , An I n q u i r y into Meaning and Truth, Penguin Books, Baltimore, Maryland. Savard, J . G . ( 1 9 7 0 ) , La valence lexicale, ~i d i e r , P a r i s . ~x p l o r a t i o n s in semantic t h e o r y ,a t a base was first punched on cards t o be i n p u t t e d as a s i n g l e l i s t structure, with t h e d i c t i o n a r y e n t r i e s a l p h a b e t i c a l l y ordered. I t was soon e s t a b l i s h e d that this arrangement by f a r exceeded run-time storage l i m i t -a t i o n s ( u s i n g a field l e n g t h of 100,000, ) . Only ahout one f i f t h of t h e m a t e r i a l could be accomfnodated a t one time without exhausting t h e available space. T h e r e f o r e t h e dictionary was s p l i t i n t o f i v e i n d i v i d u a l List s k r u c t u r e s , and t h e correspofidbng card imaqes were stored on disk as f i v e s e p a r a t e f -i l e s . These were brought i n , one a t a time, f o r p r o c e s s i n g ss needed. Recause of space l i m i t a t i o n s , also processed d a t a and i n t e r m e d i a t e r e s u l t s had t o \"I be p u t i n e x t e r n a l s t o r a g e d u r i n g r u n t i n e and, of c o u r s e , between runs, t h e r e f o r e more f i l e s had t o he created as de.;crihzd l a t e r . Thus, a g r e a t d e a l of programming effort went into f i l e manipulation. The purpose o f t h e first program, d e s i g n a t e d AMALEX, was simply t o d i s p l a y t h e dictionary. I t Y i r s t reads t h e function words from the cards and stores them i n the form of a 121x2 array. (The width of the a r r a y is 2 because many function words are l o n g e r than 10 c h a r a e t e r s . ) Using a f u n c t i o n READLS, the program reads t h e dictionary and s t o r e s 15: in t h e form of a l i s t structure as described above. On t h i s occasion, it also measures t h e space r e q u i r e d f o r the d i c t i o n a r y . I t was found that a field length of more t h a n 235,680, locations ~m u l d he needed to accommodate the entire data base. A subroutine c a l l e d RITELS prints out the d i c t i o n a r y , s p e c i f y i n g each e n t r y by t h e d e f i n i t i o n in the form of at most 10 words to the l i n e . The r o u t i n e a l s o checks t h e operator code numbers in the third'-level sublists and replaces these in t 3 e p r i n t o u t by the appropriate f u n c t i o n tmrds from the array. The d i c t i o n a r y was p r i n t e d out in f o u r separate rvns as t h e d i c t i o n a r y was initially divided i n t o f o u r l i s t s . Since the ANALEX program does no f u r t h e r processing and accumulates no new l i s t s , no storage problems arose. It was n o t until later t h a t it was established that a d i v i s i o n into five p a r t s was necessary t o perform subsequent o p e r a t i o n s i n t h e spacea v a i l a b l e . T h e f i r s t p r i n t o u t s were carefully examined f o r punching errors and omissions. Detected errors ware corrected and t h e f i l e s were updated accordingly. The actuaI working program is named COVSET. If the entire data b a s e were o n e single l i s t and if time were a v a i l a b l e indefinitelv, A t h i s pro-gram would do the complete work in a single r u n . In t h i s case, i t would print a fable of corresponding vand % v a l u e s for a g i v e n v a l u e of N , would r e d u c e the v a l u e of I and p r i n t o u t a n o t h e r table, etch , and repeat t h i s for a l ldesired va l u e s of N. -This, of course, could not be done because, i n the f i r s t p l a c e , o n l y one of the f i v e parts of t h e d i c t i o n a r y could h e worked on a t a t i m e and, i n thse second p l a c e , the program had to be run i n time i n c r e m e n t s of 6 0 0 s or l e s s , which was the set t i m e l i m i t , The p r i n c i p a l r o u t i n e i n COVSET i s c a -l l e d COVRYG, w h i c h computes t h e v a l u e s of v f o r g i v e n v a l u e s of v 2 e i n h e r e n t l y c o n t i n u o u s orogram cannot klc3 run continuuously, a few c o n t r o l variables a r e needed t o provide c r i t e r i a for i n t e r r u p t i o n and t o t r a n s f e r i n f o r m a t i o n from one r u n t o t h e next. These a r e r e a d from c a r d s i n the beginning of the routine. A reference value LSTRCF i s used t o control t5e spBcing of the r e c o r d i n g s of v and because too close s p a c i n g would S -introduce random i r r e g u l a r i t i e s into t h e o t h e r w i s e s m o o t h l y cllanging tendency. The reference is automatically updated after very p r i n t o u t of the. 5 and # v a l u e s . D u r i n g the analysis of -Flow diagram of COVRNG.",
                "num": null,
                "uris": null
            },
            "FIGREF24": {
                "type_str": "figure",
                "text": "l l dictionary, the reference was incremehteit hy 200; l a t e r , , in t h e processing of the reduced dictionarv, criterion is needed f o r i n t e r r u p t i n g the program h e f~r e it exceeds the time l i m i t .An estimated increase in v s WC?S i n i t i a l l y used f o r t h i s purcpose. A value '3AXLCFJ vas i n n u t and 5compared r i t h it every time a new word w a s acldcd to t\"l s e t .\\%en t h e coun-t reached t h e reference v a l u e , t h e program :Jasdiscontinued. 0 t h e average, about 1 5 words per ptun could hc added to the covered set. Later it was found that b e t t e r c o n t r o l could he exercised Ilv counting the number of times that a new section of t h e dictionary was brought i n for processing. A Value !WXW,P was read Ln and when the above counter, s t a r t i n g from O, reached this va'lue, t h e run was interrupted. The variables KNTCVD and KNTCNG are counters f o r v and v R , transferred from one rur. to the o t h e r . The value of KNTPRT i n d i c a t e s t h e s e c t i o f i of t h e dictionary currently under investigation. The variable IrtCONT is s e t to 0 f o r t'le very f i r s t run far each N value. This tells the r o u t i n e to set up new l i s t a fox -Covered L i s t , Covering L i s t , and a so-called Waiting List. In a l l successive runs its value i s 1 , i n d i c a t i n g t h a t the program must bring these l i s t s i n from t h e external file. The r o u t i n e exmines the current. section of the dictionary, entrymby e n t r y . In the first series of r u n s , it deals w i t h one o f t h e f i v e sections, stored in one of t h e f i v e files, i n t h e form of t h e o r i g i n a l card images. A sixth file was created f o r s t o r i n g a l l t h e lists generated by the program. Idhen t h e d i c t i o n a r y was later reduced ( f o r reduced values of nr , t n e C c o r r e s p o n a l n g s e c t i o n s of t h e reduced dictionary were a l s o stored in that s i x t h file. I f t h e c u r r e n t entry i s an element of the Sas.ic vocabulary (type 2) , the routine bypasses it and takes t h e next entry. Tflis can be dane in t h e processing of t h e f u l l dictionary because all these words o c c u r in t h e definitions and will c e r t a i n l y he caught l a t e r . T h i s i s no longer so in processing the reduced d i c t i o n a r y because t h e words in the definitions of which they occur may have been eliminated. I n t h e latter case, t h e r e f o r e , this tvpe 0.f a word i s immediately added t o b o t h t h e Covered List and the Covering L i s t (it always covers i t s e l f ) . I f t h e current entry i s a word that does n o t occur i n any d e f i n i t i o n (type O ) , it i s being encountered t h e f i r s t t i m e , and we a r e sure t h a t it i s not alteady on the Covered-L i s t ; hence, t h i s question need not be asked. Otherwise the routine tests if the word is already on t h e Covered List, which may well he t h e case hecause the word may have occurred earlier in the definition of another word. If so, t h e routine proceeds to t h e next ward i n t'le d i c t i o n a r y . If t h e word is not found on the Covered L i s t , i t is p u t there, and KNTCVD is incremented. Then a l l the words in tho definition of the word in q u e s t i o n are put on t h e Waiting List, which is subsequently processedd This is necessary hecause o f t h e adopted p r i n c i p k e t h a t a l l t h e covering :vords n u s t t'lemselveq be covered. An entry in the r3 versvR # tahle i s meaningful -o n l y i f t h i s c o n d i t i o n i s s a t i s f i e d . The current d i c t i o n a r y e n t r y i t s e l f . is recorded as t'le valug of the variable DREF, which p a s s e s the information on, from one r u n to the n e x t , where in t h e d i c t i o n a r v t h e program is c u r r e n t l y in action. The r o u t i n e then examines the Waiting L i s t , word by vord. I f the current vmrd is already on the Covered L i s t (it mav have Occurred earlier in t h e dictionarv), t h e r o~k i n e c3ecks if it is also on t$e Covering L i s t (it may not he hecause it has n o t v s t occurred in the d e f i n i t i o n of another swrd) . If not, it i s putthere, and KNTCNG is incremented. A11 words on the Waiting L i s t come from definitions and must therefore he added t o t h e C o w r i n g L i s t .",
                "num": null,
                "uris": null
            },
            "FIGREF25": {
                "type_str": "figure",
                "text": "~f the c u r r e n t ptord i s n o t on the Covered List, it must o b v i o u s l y be p u t sthere. F i r s t , however, t h e routine t e s t s i f t h e word occurs in t h e s e c t i o n of t h e d i c t i o n a r v c u r r e n f l v i n s t o r e by checking whether i t s numerical v a l u e is between those of t h e f i r s t and t h e l a s t word of t h e s e c t i o n . I f the word i s n o t t h e r e , t h e r o u t i n e postpones i t s processing and takes t h e n e x tw o r d from t h e Waiting L i s t because i t i s more econoznical t o process f i r s t a l l the words available i n t h e d i c t i o n a r v s e d t i o n present t h a n t o read i n o t h e r sections of the d i c t i o n a r v as t h e words d i c t a t e it (memory swapping is* cxpensive) . Should t h e word be i n t h a t section, t h e r o u t i n e adds it t o the Covered List, increments KNTCVD, and a c t u a l l y looks for t h e w o r d i n the d i c t i o n a r y . I f it does nok find it, it g i v e s an e r r o r m e d a g e , p r i n t s o u t the questionable word, and terminattbs t h e r u n . T h i s way t'he remaining punching errors in the d a t n h a s e w e r e d e t e c t e d , and a ferv words were found missing (due t o human error q u r i n g t h e c o n s t r u c t i o n of t h e d a t a base when it wasforgotten to e n t e r words that acutally occured i n d e f i n i t i o n s ) .The f i l e s were updated a c c o r d i n g l y .",
                "num": null,
                "uris": null
            },
            "FIGREF26": {
                "type_str": "figure",
                "text": "If t h e word i s found, the r o u t i n e adds a l l t h e words i n i t s d e f i n i t i o n to t h e Waiting L i s t , t h e n i n v e s t i g a t e s i t s presence on the Fovering List, and proceeds as described before.When t h e bottom of the Waiting ~1 s t i s reached and the l i s t i s not empty, t h e words remaining on it must be i n o t h e r s e c t i o n s of t h e d i c t i o n a r y . The section present is then erased and the next s e c t i o n i s brought i n (if the c u r r e n t one is s e c t i o n 5, s e c t i o n 1 is read in). The processingof t h e Waiting L i s t now starts from t h e beyinning and continues as described above. If the Waiting List is finally empty, and K?ITCVD equals or exceeds LSTREF, the r o u t i n e i n c r e m e n t s LSTREF by the prescriber? amount, and prints t h e values of KT!TTCVD and I3VTCTTG. If t h e couflt i s less than t h e reference value, the r o u t i n e simnlv proceg'ds. I n any case, i t tests if t h e proper section of t h e dictipnarvhappens to he in the store (it knows t h a t hvthe value of KNTPRT) . If it does n o t , the section present' is erased a n 3 the right section is read in. Next t h e routine looks for the word 3t v11ic5 it had w v i o u s l y stopped t r a c i n g t h a dictionary ( i t knows t h a t l?y t\\e c o n t e n t s o f DREF). An error message has been rrovidedfor t h e case i n which it does n o t f i n d t h e reference for some r e~s o n . FortUnately, t h e program never made use of t h i s message. A f t e r finding the reference, t h e r o u t i n e takes the n e x t v~ord from t h e d i c t i o n a r y and proceeds as alread d e s c r i b e d . When the r o u t i n e reaches t h e bottom of t h e d i c t i o n a r y , it t e s t s if it is the last s e c t i o n . If n o t , t h e n e x t section i s processed as described. A t the end of t h e last s e c t i o n the r o u t i n e prints the final values of v and v and v i t h this t h e S R ' -prbcessing is f i n i s h e d for a given value of I) N.",
                "num": null,
                "uris": null
            },
            "FIGREF27": {
                "type_str": "figure",
                "text": "s c r i p t i o n involves countless r u n s . I n t e r r u p t i o n c r i t e r i a a r e tested a t a p p r o p r i a t e places, and t h e processing i s discontinued a c c o r c l~n g l y . Whenever a run i s t e r m i n a t e d , the three compiled lists a r e saved ??y s t o r i n g t ' l n n in t ! e external file (we shall c a l l it File 9 f o r t\\e sake of convenience) . The c o n t r o l parameters and reference v a r i a b l e s a r e p r i n t e d out,. The data cards are changed a c c o r d i n s l y , for i n p u t t o t h e next run. The f i r s t series of runs was perZomed w i t h t h o ell 11d i c t i o n a r y , f o r which the maximum d e f i n i t i o n length i r is 22. In dhe following qeries of runs N was gradually decreased.",
                "num": null,
                "uris": null
            },
            "FIGREF28": {
                "type_str": "figure",
                "text": "n also necessasv t o reduce the d i c t i o n a r v hv eliminating all & words with d e f i n i t i o n length greater t h a n t h e 'curre3t hl, t !~e n eliminating 1 words containing them in t h e i r definitions, subsequently eliminating all words the definitions of vthic\\ c o n t a i n the latter, etc. T h e program c a l l s another qajor subroutine, named DICRED, to carry out this operation. The routine is hasicallv simple; w h a t makes i t appear complicated i s the m a n i p u l a t i o n of t\\e files. It was found to be most convenient to search one section of the d i c t i o n a r y per run.",
                "num": null,
                "uris": null
            },
            "FIGREF29": {
                "type_str": "figure",
                "text": "the data cards, t h e routi'ne reads a reference parameter called KYTSCT, which indicates the !lBighcst consecutive s e c t i o n number t h a t h a s been s e u c h e d . The c o n t r o l variable I D R P h a svalne 0 at input; t h e r o u t i n e . changes it to 1 if any w,qrds were r e m o v e d from t h e section c u r r e n t l y Seing searched, ot3erwise it ternsins 0 at output. The variable KNTRPT shows the n u r n h~r of the s e c t i o n currently being searched. #The parameter INDFIL is s e t to 0 every time a new section is searched t h e first time. T h i s t e l l s t h e r o u t i n e t o b r i n g rn khe section i n d i c a t e d hv KVTSCT. If its value is 1, the s e c c i o n to be read is i n d i c a t e d hy KMTPPT. The reduced sections are stored i f T i l e c o n s e c u t i v e l y . I f KNTRPT i s less than KNTSCT, the sections f o l l o~d n g the one currently searched are stored on a temporary f i l e because t h e l e n g t h of t h e one b e i n g searched mav decrease. Not u n t i l t h e search h a s ended and t h e c u r r e n t section has been stored back at its proper place are the following gections transferre2 back to F i l e 9.. For example, if KNTRPT = 1 and IZNTSCT = 5 , t h e n sections 2, 3 , 4 , and 5 are stored away.",
                "num": null,
                "uris": null
            },
            "FIGREF30": {
                "type_str": "figure",
                "text": "List. In the quhsequent r u n s the r o u t i n e read3 i n thz R e m o v a l . L i s t f r o m t h e file. The routine examines the definition lengths of the e n t r i e s in the current s e c t i o n . i t e m h y item. The entries the definition l e n g t h of which is greater than the s e t Nv a l u e are put o~ t'ls Removal List dfid d e l e t e d from t!le d i c t i o n a r v . T5e v a l u e of I P R D i s .set t n 4 if such entries are found. The remove2 words are printed o u t f o r reference. Then t h e d i c t i o n a r y i s searched artd a l l definitions are checked a g a i n s t the items on t h e Removal List. I f a c l e f i n i t i p n c o n t a i n i n g a removed word is found, the respectiv~ e n t r y i t s e l f is added to t h e Removal L i s t and sul\\sequently deleted from tho d i c t i o n a r y . If a search results in any new additions to the Removal List, t h e search is repeated. This is continued u n t i l no new d e l e t i o n s occur. A f t e r the ILL n-th section has been p r o c e s s e d t h e first time and i f d e l e t i o n s have o c c u r r e d , KNTRPT i s set to 1 ,2, . . , ;r",
                "num": null,
                "uris": null
            },
            "FIGREF31": {
                "type_str": "figure",
                "text": ", d e l e t i o n s ( I D W s e t to I ) , t h e sequence is repeated. This i s continued u n t i l IDRP remains i n all n runs. LI A t the end of every r u n , after the temporarilv --saved dictionary s e c t i o n s nave bee restored, t h e Removal List is stored as t h e l a s t i n F i l e 9. Then t h e values of the key variables are printeH out. r the next run. After t h e sequence of r u n s w i t h KNTSCT = 5 h a s been coqpleted, the operation i s f i n i s h e d . The r e d u c t i o n was aarried o u t with values of N equal t o The valbp 10 W~S . t r i e d a f t e r 16, but the r e s u l t i n g r~d u c t i o n was too s l i g h t so t h a t t h e series was discarded and the value R was us& insteati. A t N = 4 . t h e size r a t i o was already s o close t o u n i t y t h a t a further r e d u c t i o n to 2 would no longer have been v e r y i n f o r m a t i v e . A l l s e c t i o n s of a l l the s u c c e s s i v e l v redu-ged dictionaries have been preserved o n F i l e 9. P r e s e n t l y F i l e . 9 has 1 5 lists, each e n d i n g w i t h an EOF. The 1 6 -t h c o n t a x n s t h e Covered List, t h e Covering List, and the Waiting List from the l a s t r u n . These three are not separated by EOF1s as there was no necessity f o r separati~g them. This l i s t c o l l e c t i o n has no g a t t i c u l a r importance. The remaining s u b r o u t i n e s i n the program are short auxiliary r o u t i n e s for aiding t h e principal r o u t i n e s where needed. The f u n c t i o n INPUTL reads in a list structure from t h e card images on file, w i t h o u t p r i n t i n g o u t t h e lisk as does the original S L I P routine. It constructs erasable l o c a l sublists. I t i s v i r t u a l l y t h e same routine as READLS used by ANA-LEX. RESTOR i s e q u i v a l e n t t o t h e SLIP subroutine of the same name except that it does n o t leave a SLIP c e l l w i t h a list name as datum floating in the m a i l a b l e space. (The l a t t e r tends t o cause program termination w i t h an error message t o t h e effect that a list was r e q u i r e d but not found.) The subrolltine SKIP is needed for convenient a c c e s s i n g of t h e various l i s t s i n F i l e 9. Finally, th$ f u n c t i o n DLTLST i s the most e f f e c t i v e means s o far t r i e d for deleting list structures b u i l t by t h e SLIP r o u t i n e BUIBPL. (It does not comp1etel.rdestroy them, however, and i f BiJINPL is used reneatedlv, -. t h e store is s t i l l gradually filled v i t h r e s i d u e s t h a t rake available space unavailable. ) APPENDIX I1 Some Ideas f o r the Program to Investigate the R e l a t i o n s h i p Coverinq Set Size versus ~l a x~m u m D e f i n i t i o n Lenqth The second proposed problem, viz. f i n d i n g vR as. a f u n c t i o n of N for f i x e d v a l u e s of vS, i s diccussed now. T h i s w i l l he a t a s k of proportions no less t h a n t h e p r e s e n t , except f o r c o n s t r u c t i o n of t h e data base. The following ~rocedure, represented hy a s i m p l i f i e d flow c h a r t in F i g u r e 4, i s suggesteci f o r c a r r y i n g out t h i s task. INSERT FIGURE 4 ABOUT HER3 The program starts with known v a l u e s of Y and v~ (in t h i s case 2 2 and 1 , 4 6 4 , r e s p e c t i v e l y ) . I t first replaces words in F having a definition length of 1 (except, of course, t h o s e defined by themselves) by t h e i r definition i n all d e f i n i t i o n s . Then the program l o o k s f o r words of s h o r t d e t i n i t i o n length in R ( x = m 2,3,4, etc.) . I t s u b s t i t u t e s their d e f i n i t i o n f o r them i n a l l d e f i n i t i o n s and counts them out from v . R S i m u l t a n e o u s l v , it .. keeps track of possible i n c r e a s e in-N due t o th3.s process and 4 .-Fl.orv diagram f o r e s t a b l i s h i n g N-v relations R records t h e fmlue. The process is repeated w i t h reclucecl dictionaries, w h i c h have different vs values. As pointed out earlier it is not suggested that d e f i n i t i o n s so created are usable or acceptable to t h e speaker of a natural language.",
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            "TABREF0": {
                "content": "<table><tr><td>Some 1 3</td></tr><tr><td>Aspects</td></tr></table>",
                "text": ". . . . . . . . . . . . . problems of lexical relatedness . . . . . . . . . . . . Polysemy and homonymy . . . . 11 2 . Synonymy . . . . . . . . . . . . . . a . m . m . . . . . . . . . . . . . . . . . . . . . . . . Definitions 13 . . . . . . . . . . . . . of the science of dictionary 1 . General concepts . . . . . . . . . . . . . . . . . . The problem-of coverage . . . . . . . . . . . . . . .",
                "type_str": "table",
                "num": null,
                "html": null
            },
            "TABREF1": {
                "content": "<table><tr><td>Covered-Covering R e l a t i o n s h i p s</td></tr></table>",
                "text": "",
                "type_str": "table",
                "num": null,
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            }
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