{ "paper_id": "C65-1010", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T13:12:17.476602Z" }, "title": "", "authors": [ { "first": "Kenneth", "middle": [ "E" ], "last": "Llarper", "suffix": "", "affiliation": {}, "email": "" } ], "year": "", "venue": null, "identifiers": {}, "abstract": "", "pdf_parse": { "paper_id": "C65-1010", "_pdf_hash": "", "abstract": [], "body_text": [ { "text": "In a given text, each word bears a given syntactic relationship to a finite number of other words; e.g., a finite number of words (nouns and pronouns) appear as \"subject\" for each active verb;", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "another group of nouns and pronouns are used as \"direct object\" of each transitive verb; other words of the class, \"adverb,\" appear as modifiers of a given verb.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "In each instance we may speak of the related words as SRW of a given verb, so that in our example three different ~ of SRW emerge; a given SRW is then defined in terms both of word class and specific relationship to the verb. (A given noun may of course belong to two different types of SRW, e.g., as both subject and object of the same verb.)", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Distributionally, we may compare two verbs in terms of their SRN. The objective of the present study is to test the premise that \"similar\" words tend to have the same SRW. This premise is tested, not with verbs, as in the l,arper above example, but with nouns. Our procedure is (i) to find in a given text three types of SRW for a small group of nouns, (2) to find the number of Sill; T shared by each pair of nouns formed from the group, and (3) to express the \"similarity\" between individual nouns) and groups of nouns,", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "as a function of their shared SRI~. Another example: it might turn out that in a given text the nouns \"a\" and \"b\"", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "(\"avocado\" and \"cherry\") share such adjective modifiers as \"ripe,\" whereas nouns \"c )' and \"d\" (\"chair\" and \"furniture\") have in common the adjective modifier \"modern.\" These facts would lead us to conclude that \"a\" and \"b\" are similar, that \"c\" and \"d\" are similar) that \"a\" and \"c\" are less similar, etc. Table 1 ) a'ere presumed to form different semantic groupings. A listing is produced for each of the TWs (see Table 2 , lists is also shown in Table i , together with the total number of SRW for each TW (List 4). We stress the fact that these numbers refer to different words used as SRW; the repetition of a given SRW (for a given SRW type) was not recorded.", "cite_spans": [ { "start": 95, "end": 120, "text": "(\"chair\" and \"furniture\")", "ref_id": null } ], "ref_spans": [ { "start": 307, "end": 314, "text": "Table 1", "ref_id": "TABREF2" }, { "start": 417, "end": 424, "text": "Table 2", "ref_id": null }, { "start": 450, "end": 457, "text": "Table i", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "\"", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "2. Each Tl~ was automatically compared with every other TW, with respect to their shared SRW, i.e., in terms of the words i~ Lists I, 2, and 3 of the \"SRW Detail Listing.\"", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "A new listing, \"Similarity Ranking by T%~',\" is then produced (see Table 3 for the T~, VYCISLENIE = calculationl). This listing shows for each TW the number of shared SRW of each of the three types (NI, N2, and N3, verbsj where TW is subject; verbs, where TW is direct object; prepositional phrases as dependents, or governors, of TW; nouns joined to TW through coordinate conjunctions (i.e., \"apples\" and \"grapes\" are said to be more similar if \"apples and oranges\" and \"grapes and oranges\" occur in .............. L ......... In addition, unless at least two, and preferably all three, types of SRW are well represented for a given TW, the SC for that noun will tend to be skewed. As examples, we note all nouns in Croup 6 (for which the 1,3 column predominates), and the nouns in Group lO (for which the L2 column predominates).", "cite_spans": [], "ref_spans": [ { "start": 67, "end": 74, "text": "Table 3", "ref_id": "TABREF4" }, { "start": 501, "end": 527, "text": ".............. L .........", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "llarper 7 ,-1 N ~ < ~P Z Z u.l D II =d 0 0 0 0 C (D 0 0 (D C 0 e~ ,-, 0 0 0 0 0 C~ 0 wO WD 0 (D 0 0 0 (D 0 0 0 C) o o 0 0 0 0 0 0 0 0 ~ o O o 0 0 0 0 0 C 0 0 0 0 0 0 0 0 0 c'3 (D 0 o 0 0 0 o C:, o C, c o o 0 o 0 C ,,,t ,, ~ * ., ? - O\" \u2022 o g o e d * ii ii ii o 0 o 0 \" \u00b0 g \u00b0 \u00b0 L \u00b0 . 2\" ~ ~, Z ~- ,0 Ii Z ,4' Z ~.~ Z ~.~ Z u.~ o, Z Z Z C Q 0 g ~ ,,==~C\" .=gC:,,= tiarpcr ,.. t.') >- LD }--4 >.~ < , \u2022 \u2022 \u2022 .~ .... \u2022 \u2022 ,~ \u2022 , , , \u2022 \u2022 \u2022 \u2022 , .... , , J .~J 3: 2\" ~ C C 0 C ~--. C C 0 C. \"2_ e\" .'? C \"~ C C C C..~ C C \"T_ C ~ C LD .\" \"D ~ C ~ C C CC C TC CCC .. ~ C CDC ~ OC COO~C~ cc=o=z CC~C ~CC~CC C~OCCCCCC~C~C~C C ~ C C GC C C ~ C C C GC ~ ~ ~ ~'C C C~C~CCC~COGC~CC~COC of", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "In effect, these nouns are \"deficient\" in certain types of SRI;', and require special handling.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": ",t", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "On the printout, \"Ranking of Tl~-Pairs by SC, a number of noun pairs appear at the top end of the scale although the total number of shared SRW is small (i.e., the value of colurnn \"NA\" (see Table 4 ) is \"1,\" \"~,.,\" or \"3.\"", "cite_spans": [], "ref_spans": [ { "start": 191, "end": 198, "text": "Table 4", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "The SC may be high, because the product of the frequencies is relatively low. Our policy has been to discount these pairs on the grounds that the value of \"NA\" is significant in determining the similarity between two TWs. The minimum value for NA was arbitrarily set at four.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Keeping in mind these anmndations to the data in mind,", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "We proceed to the discussion of the noun-pairs characterized by highest S(:. For purposes of discussion, we propose to set the t]~reshold", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "at .00100--a rigorously high figure.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "After eliminating pairs whose NA value is less than 4, we find 38 p,~irs whose SC lies in the range .00100 to .01~337 (Table 5 ).", "cite_spans": [], "ref_spans": [ { "start": 118, "end": 126, "text": "(Table 5", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "(Z],e first two zeroes are dropped.)", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "The reader may draw his own conclusions about the degree of similarity between the nouns in any given pairing. For purposes of discussion, we will refer to the pairings in terms of our preliminary groupings (Table I) .", "cite_spans": [], "ref_spans": [ { "start": 207, "end": 216, "text": "(Table I)", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "The following intra-and inter-Group pairings are observed in Tab le 5 :", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Nouns of Group 1 pair with nouns of Group I, 2 2 I, 2, i0 3 4 5 5 4, 5, 6, 7 6 5, 6, 7 5, 7 8 9 9 i0 2, I0 ii 5, Ii", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "We note that no pairings appear for nouns of Groups 3 and 8. All other groups except Group 4 are represented by intra-group pairings; to this degree, our expectations are fulfilled, i.e., the data supports our a priori feelings for the similarity between words. The amount of inter- group pairing may indicate either that the data is inconclusive, or that our original groupings were too narrow.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "In fact, two larger groups emerge: one composed of Groups 1 and 2 (perhaps including Group 1O), the other composed of Groups 4, 5, 6, and 7. This tendency is more marked if we lower the SC threshold from .00100 to .00070, thereby adding a total of 28 pairs to the number listed in Table 5 . For example, nouns of Group 1 are found to pair with those of Group 10, and nouns of Group 4 pair with those of Groups 6 and 7.", "cite_spans": [], "ref_spans": [ { "start": 281, "end": 288, "text": "Table 5", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "The data is not statistically conclusive, but strongly suggests the emergence of the two major groups mentioned above.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "The amalgamation of Groups 1 and 2 can easily be defended on semantic grounds; since Group 10, as noted above, is subject to aberrant behavior (because of the very high number of noun dependents), its inter-relation with Groups 1 and 2 may not be taken seriously. Groups 4, 5, 6, and 7, which include the names of chemical mixtures, classes of elements, individual elements, and components of elements, may be taken together semantically as a single sub-class of \"object nouns.\" The physicist tends to say the same things about all nouns in this group.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "One of tile 38 pairs listed in Table 5 appears to contradict expectation: \"liquid\"/\"problem\"(Groups 5 and Ii).", "cite_spans": [], "ref_spans": [ { "start": 31, "end": 38, "text": "Table 5", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "It should also be noted that the noun dependents of Group i0 nouns serve a \"subjective\" rather than \"objective\" function.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "If we had distinguished between the syntactic function of the noun dependent, TWs of Group I0 would be only weakly similar to TWs of Groups 1 and 2.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Tile four SRW shared by those two nouns include the adjective \"certain\" and the noun governor \"number.\" The non-discriminatory (\"promiscuous\") nature of these two SRW is perhaps obvious, and one of the refinelaents that should be introduced in future studies is the neglect of such words as \"significant\" SRI~. (Tile study of \"promiscuity\" in adjectives is referred to in Reference 4.) At the present, experience suggests that distortions introduced by such words are minimal if the number of SRW is sufficiently large.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Our general conclusion is that, with a few anomalies, the 66 pairings for which the SC Is .00700 or higher meet with our expcctations.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Another aspect of the question remains: many nouns with presumed similarity arc not represented on the high end of the SC distribution curve. (If we lower the threshold to include such pairs we shall also encounter many non-similar pairs.) One way of dealing with this problem is to consider the most highly correlated pairs that nouns in each Group form, whether or not the SC is \"significantly\" high.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "In lieu of presenting this information in full detail, we show in Table 6 the most closely correlated pairs for a representative noun from each of the Groups (excepting Groups 3, 4, and 8).", "cite_spans": [], "ref_spans": [ { "start": 66, "end": 73, "text": "Table 6", "ref_id": "TABREF9" } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "The most striking aspect of Table 6 is the repetition of intra-and inter-Group pairings noted in Table S for high-SC pairings. In other words, the relative value of the SC appears to be as significant as the absolute value.", "cite_spans": [], "ref_spans": [ { "start": 28, "end": 35, "text": "Table 6", "ref_id": "TABREF9" }, { "start": 97, "end": 108, "text": "Table S for", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Z C C, E--, 0 u 0 u' o C--. X 0 < ,--,", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "This result was certainly not expected, and perhaps indicates a greater sensitivity in our measurement procedures than we would have thought reasonable. ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "(LZ)", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Noun Governors: Table 7 shows that eighteen SRW appeared for calculation I Of these, one half (nine) also appeared as SRW for both determination and measurement. It would seem that the \"togetherness\" of these three TWs is strengthened by this feature, which we term \"recurrence of SR;V.\" We have no ready formula for determining that recurrence is or is not significant in a given situation. In general, the nature and behavior of individual SRIV remain to be studied, so far as their relevance to our problem is concerned.", "cite_spans": [], "ref_spans": [ { "start": 16, "end": 23, "text": "Table 7", "ref_id": null } ], "eq_spans": [], "section": "", "sec_num": null }, { "text": "We conclude that there is considerable agreement between the results of our experiment and an a priori feeling for the similarity of words. ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "CONCLUS IONS", "sec_num": "4." }, { "text": "~,arper", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null } ], "back_matter": [], "bib_entries": { "BIBREF1": { "ref_id": "b1", "title": "The RAND Corporation, R~I-2538", "authors": [], "year": 1960, "venue": "Ap'ril", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Determination, The RAND Corporation, R~I-2538, Ap'ril 1960.", "links": null }, "BIBREF2": { "ref_id": "b2", "title": "Basic Principles and Technical Variations in ,qentence-Struc~ure Determination, The RAND C0rporation, P-1981", "authors": [ { "first": "D", "middle": [ "G" ], "last": "Tlays", "suffix": "" } ], "year": 1960, "venue": "", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "tlays, D. G., Basic Principles and Technical Variations in ,qentence-Struc~ure Determination, The RAND C0rporation, P-1981, April 1960.", "links": null }, "BIBREF3": { "ref_id": "b3", "title": "A Study of the Combinatorial Properties", "authors": [ { "first": "K", "middle": [], "last": "Llarper", "suffix": "" } ], "year": 1963, "venue": "Mechanical Translation", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "llarper, K. ti., \"A Study of the Combinatorial Properties \" Mechanical Translation, August 1963, of Russian Nouns, .....", "links": null }, "BIBREF4": { "ref_id": "b4", "title": "Procedures for the Determination of Distributional Classes", "authors": [ { "first": "K", "middle": [ "E" ], "last": "Tlarper", "suffix": "" } ], "year": null, "venue": "File RAND Corporation,-RM22~13, Janu d ary' 196i", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "tlarper, K. E., Procedures for the Determination of Distri- butional Classes, \"File RAND Corporation,-RM22~13, Janu d ary' 196i.", "links": null } }, "ref_entries": { "FIGREF0": { "text": "SRW Detail,\" for an example of the TW, VYCISLENIE = calculation 1), showing tile different words used as adjective dependents (List i), noun dependents (List 2), and noun governors (List 3). Tile number of words on each of these", "type_str": "figure", "uris": null, "num": null }, "FIGREF1": { "text": "text). Some of the holes in our tea strainer are: the neglect of the case of the noun dependent of TW, or the .... t . . . . . . i ............. 4 .................. :: ............ : ..............", "type_str": "figure", "uris": null, "num": null }, "FIGREF3": { "text": "); SILA (force); FORMA (form). ZRENIE (view) ; REZUL'TAT (result) ; ~NO~T~--(pos s ib i I i ty);-~__ (method).", "type_str": "figure", "uris": null, "num": null }, "TABREF0": { "html": null, "text": "A study was r~ade of tile degree of similarity between pairs of Russian nouns, as expressed by their tendency to One of the goals of studies in Distributional Semantics is the establishment of word classes on the basis of the observed behavior of words in written texts. A convenient and significant way of discussing \"behavior\" of words is in terms of syntactic relationship. At the outset, in fact, it is necessary that we treat a word in terms of its Syntactically Related Words (SRW).", "num": null, "type_str": "table", "content": "
[larper 1
MEASURENIiNT OF SIMILARITY BETWEEN NOUNS
I.INTRODUCTION
occur in sentences with identical~,,ords in identical
syntacticrelationships.A similaritymatrix was prepared
for forty nouns; for each pair of nouns the number of
shared (i) adjectivedependents,(ii) noun dependents,and
(iii)noun governors was automaticallyretrievedfrom
machine-processedtext.The similaritycoefficientfor
each pair ~;as determined as the ratio of the totalof
such shared ~'ords to the product of the frequenciesof the
two nouns in the text.The 78~ pairs were ranked according
to this coefficient.The text comprised 12(1,~00 running
words of physics text processed at The RAND Corporation;
the frequenciesof occurrence of the forty nouns in this
text ranged from 42 to 328.
The resultssuggest that the sample of text is of
sufficientsize to be useful for the intended purpose.Many
noun pairs with similar properties(synonymy, antonym),,
derivationfrom distributionallysimilar verbs, etc.)are
characterizedby high similaritycoefficients;the converse
is not observed.The relevance of various syntacticrela-
tionshipsas criteriafor meas~rement is discussed.
" }, "TABREF2": { "html": null, "text": "", "num": null, "type_str": "table", "content": "
gives one possible grouping of these words; the
criteriafor grouping are more or less obvious, although
the reader may easily form differentgroups, by expanding
or contractingthe groups that we have designated.The
only purpose of grouping is to provide a weak measure of
control in the experiment:if two nouns are found to be
similar in terms of their SRN, we should like to compare
this finding with some intuitiveunderstanding of their
similarity.(For convenience, we shall refer to the 'rWs
by their English equivalents.)
Two nouns may be compared with reference to several dif-
ferent types of SRW. ilere, we have chosen to iimit our
comparison to three types:t.t}e adjectivedependents (in
either attributiveor predicativefunction),the noun
depend.ents (normally, but not necessarily,in the genitive
case in Russian),and the noun governors (the TN is nor-
mally, but not necessarily,in tile genitive case).Strictly
speaking, the syntacticfunction of the SRIq should be taken
into account.In ignoring this factor, we are consciously
permittingcertaininexactitudes,on the premise that the
distortionsintroduced into measurement will not be severe.
The task of manualiy retrievingSRW for each occurrence
of the 40 TWs, and of comparing each TW with every other
TW, is too tedious to be attempted.The aid of the computer
was enlisted,in two ways,
" }, "TABREF3": { "html": null, "text": ". Through automatic scanning of the text, each occurrence of tile 40 TWs was located, and in each instance the identity (word number) of relevant SR~V was recorded.", "num": null, "type_str": "table", "content": "
39 TEST NOUNS
" }, "TABREF4": { "html": null, "text": "), the total number of shared SR%~ (NA), and a measure of similarity for the pairs, herein designated as the Similarity Coefficient (SC). The SC is a decimal fraction obtained by dividing the sum of shared SRW for each pair of TWs by the product of the frequencies of the two TWs.", "num": null, "type_str": "table", "content": "" }, "TABREF7": { "html": null, "text": "", "num": null, "type_str": "table", "content": "
shows the distributionof
" }, "TABREF9": { "html": null, "text": "", "num": null, "type_str": "table", "content": "
suggests, but does not prove, the existence
of clusters (or \"clumps\") of T~s, in which the members are
closely correlated with each other, and in which no member
is closely correlated to any outside word.lee have not
yet attempted to apply clumping procedures; a better
understanding of the data is perhaps a prerequisite to this
rigorous treatment.For the present, we shall point out
a phenomenon that strongly suggests the existence of
clumps:the recurrence of the same SRI~ ~ among several TWs
with high mutual correlation.Consider, for example, that
a high 5C is found between Test Words A and B) B and C,
and A and C; if,in addition,a relativelyhigh proportion
of SRW are shared by all three Tl~s, the mutual connection
of the three words would appear to be considerablystrength-
ened.The recurrenceof SRW has not been systematically
studied)but the followingsample is offeredas an illus-
trationof the phenomenon.Below, we listall the SRW
of the three types,for the ]'I~ calculation1.The under-
lined words are those which, in addition,also served as
correspondingSRI; ~ for two other T;is (determination, and
measurement ) that are highly correlatedto each other and
to calculation1.
" } } } }