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"paper_id": "P84-1011",
"header": {
"generated_with": "S2ORC 1.0.0",
"date_generated": "2023-01-19T08:20:44.120690Z"
},
"title": "Lexicon Features for Japanese Syntactic Analysis in Mu-Project-JE",
"authors": [
{
"first": "Yoshiyuki",
"middle": [],
"last": "Sakamoto",
"suffix": "",
"affiliation": {
"laboratory": "Electrotechnical Laboratory Sakura-mura",
"institution": "",
"location": {
"addrLine": "Niihari-gun",
"settlement": "Ibsraki",
"country": "Japan"
}
},
"email": ""
},
{
"first": "Masayuki",
"middle": [],
"last": "Satoh",
"suffix": "",
"affiliation": {},
"email": ""
},
{
"first": "Chiyeda-Ku",
"middle": [],
"last": "Tokyo",
"suffix": "",
"affiliation": {},
"email": ""
}
],
"year": "",
"venue": null,
"identifiers": {},
"abstract": "In this paper, we focus on the features of a lexicon for Japanese syntactic analysis in Japanese-to-English translation. Japanese word order is almost unrestricted and * This project is being carried out with the aid of a specia], gro~H for the promotion of scien,:.c ah,! technology from the Science and Techno]ogy Agency of the Japane:ze GovoYf~: ~,t.",
"pdf_parse": {
"paper_id": "P84-1011",
"_pdf_hash": "",
"abstract": [
{
"text": "In this paper, we focus on the features of a lexicon for Japanese syntactic analysis in Japanese-to-English translation. Japanese word order is almost unrestricted and * This project is being carried out with the aid of a specia], gro~H for the promotion of scien,:.c ah,! technology from the Science and Techno]ogy Agency of the Japane:ze GovoYf~: ~,t.",
"cite_spans": [],
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"section": "Abstract",
"sec_num": null
}
],
"body_text": [
{
"text": "Kc~uio-~ti (postpositional case particle) is an important device which acts as the case label(case marker) in Japanese sentences. Therefore case grammar is the most effective grammar for Japanese syntactic analysis.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "The case frame governed by )buc~n and having surface case(Kakuio-shi),",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "deep case(case label) and semantic markers for nouns is analyzed here to illustrate how we apply case grammar to Japanese syntactic analysis in our system.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "The parts of speech are classified into 58 sub-categories.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "We analyze semantic features for nouns and pronouns classified into sub-categories and we present a system for semantic markers. Lexicon formats for syntactic and semantic features are composed of different features classified by part of speech.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "As this system uses LISP as the programming language, the lexicons are written as S-expression in LISP. punched onto tapes, and stored as files in the computer.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "The Mu-project is a national project supported by the STA(Science and Technology Agency), the full name of which is \"Research on a Machine Translation System(Japanese -English> for Scientific and Technological Documents.'~",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "l. Introductign",
"sec_num": null
},
{
"text": "We are currently restricting the domain of translation to abstract papers in scientific and technological fields. The system is based on a transfer approach and consist of three phases: analysis, transfer andgeneration.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "l. Introductign",
"sec_num": null
},
{
"text": "In the first phase of machine translation. analysis, morphological analysis divides the sentence into lexical items and then proceeds with semantic analysis on the basis of case grammar in Japanese. In the second phase, transfer, lexical features are transferred and at the same time, the syntactic structures are also transferred by matching tree pattern from Japanese to English, In the final generation phase, we generate the syntactic structures and the morphological features in English.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "l. Introductign",
"sec_num": null
},
{
"text": "In Japan, we have come to the conclusion that case grammar is most suitable grammar for Japanese syntactic analysis for machine translation systems. This type of grammar had been proposed and studied by Japanese linguists before Fillmore's presentation.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "As word order is heavily restricted in English syntax, ATNG~Augmented Transition Network Grammar) based on CFG~Context Free Grammar ) is adequate for syntactic analysis in English. On the other hand, Japanese word order is almost unrestricted and K~l!,jlio--shi play an important role as case labels in Japanese sentences. Therefore case grammar is the most effective grammar for Japanese syntactic analysis. In Japanese syntactic structure, the word order is free except for a predicate(verb or verb phrase) located at the end of a sentence. In case grammar, the verb plays a very important role during syntactic analysis, and the other parts of speech only perform in partnership with, and equally subordinate to. the verb.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "That is. syntactic analysis proceeds by checking the semantic compatibility between verb and nouns. Consequently. the semantic structure of a sentence can be extracted at the same time as syntactic analysis.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "3. __ca.$_e_Er ame .~oYer n~ed ..by_ J:hu~/C_ll",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "The case frame governed by !_bAag_<tn and having l~/_~Luio:~hi, case label and semantic markers for\" nouns is analyzed here to illustrate how we apply case grmlmlar to Japanese syntactic analysis in our system.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "}i~ff. As a result of categorizing deep cases, 33 Japanese case labels have been determined as shown in Table I . ",
"cite_spans": [],
"ref_spans": [
{
"start": 104,
"end": 111,
"text": "Table I",
"ref_id": null
}
],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "RECipient (4l ~-Z.~ ORigin (5) ~.~-i PARmer (6) ~-~ 2 OPPonent {7) 8-~ TIMe (8)\" ~ \u2022 ~i%,~,, Time-FRom (9) B@ \u2022 ~.~.,~, Time-TO leO) ~ DURatmn (l I ) L~p)~ SPAce 02) ~ \u2022 ~.,~,, Space-FRom (13) h~ \u2022 $~.,~., Space-TO (14\") hP~ -~ Space-THrough (15) ~Z~ ~.~, SOUrce (16) ~,~,~. GOAl (17) [~ ATTribute (18) ~.{:~ \u2022 iz~ CAUse (19) ~ \u2022 ii~. ~. TOO~ (20) $~ MATerial (21) f~ ~-'~ COMponent (22) 7]~ MANner (23) ~= CONdition (24) ~] ~ PURPOse (25) {~J ROLe (26) [-~ ~ ~.~ COnTent (27) i~ [~l ~. ~ RANge (28) ~ TOPic (29) [Lg...~,, VIEwpoint (30) ,L' tt~ COmpaRison (32) ~ DEGree 5%~/~-@. 3 ~0@-~/-,5 (33l P~]~ '~ PREdicative ~ \"~,.~ 8",
"cite_spans": [],
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"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "Note:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "The capitalized letters form English acronym for that case label. the When semantic markers are recorded for nouns in the verbal case frames, each noun appearing in relation to l/2u(~'n and Kclkuio-shi in the sample text is referred to the noun lexicon.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "The process of describing these case frames for lexicon entry are given in Figure ] .",
"cite_spans": [],
"ref_spans": [
{
"start": 75,
"end": 83,
"text": "Figure ]",
"ref_id": null
}
],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "For each verb, l<ctkuio-Mtt and Keiuoudoi~-_.shi, Koktuo-shi and case labels able to accompany the verb are described, and the semantic marker for the noun which exist antecedent to that Kokuio-shL are described. Adverbs are divided into 4 sub-categories for modality , aspect and tense. In Japanese, the adverb agrees with the auxiliary verb.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "C~in~utsu-futu-shi agrees with aspect, tense and mood features of specific auxiliary verb, Joukuou-fz~u-shi agrees with aspect and tense,",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "Teido-fuku-shi agrees with gradability. Auxiliary verbs are divided into 5 sub-catagories based on modality, aspect, voice, cleft sentence and others.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "Verbs may be classified according to their case frames and therefore it is not necessary to sub-classify their sub-categories.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coac_~pt of_~_Deoendencv Structure based on Case Gramma[_/n Jap_a_D~",
"sec_num": "2."
},
{
"text": "We analyze semantic features, and assign semantic markers to Japanese words classified as nouns and pronouns. Each word can give five possible semantic markers.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Semantic Markimz of Nouna",
"sec_num": "5."
},
{
"text": "The system of semantic markers for nouns is made up of tO conceptual facets based on 44 semantic slots, and 38 plural filial slots at the end (see Figure 2 ). 9.! Measure This conceptual facet contains measure: that is, the extent, quantity, amount or degree of a thing. This facet consists of semantic slots such as Number. Unit, Standard, etc.",
"cite_spans": [],
"ref_spans": [
{
"start": 147,
"end": 155,
"text": "Figure 2",
"ref_id": null
}
],
"eq_spans": [],
"section": "Semantic Markimz of Nouna",
"sec_num": "5."
},
{
"text": "10i Time and Space This conceptual facet contains space, topography and time.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Semantic Markimz of Nouna",
"sec_num": "5."
},
{
"text": "The semantic marker for each word is determined by the following steps.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "1) Determine the definition and features of a word. 2, Extract semantic elements from the word.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "3) Judge the agreement between a semantical slot concept and extracted semantical element word by word, and attach the corresponding semantic markers.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "4; As a result, one word may have many semantic markers. However, the number of semantic markers for one word is restricted to five. If there are plural filial slots at the end. the higher family slot is used for semantic featurization of the word.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "It is easy to decide semantic markers for technical and specific words. But, it is not easy to mark common words, because one word has many meanings. ('T~WlRlr . \"TENISEI~U\" , \"TEOhLi\" , \"SOKQ\\; Ri\" and \"TEII@2~U\" ) 7} Features of /9n$lli: Subcategory of /~==5~.(: case, conjunctive, adverbial, collateral final or 2_Ill~li",
"cite_spans": [
{
"start": 150,
"end": 175,
"text": "('T~WlRlr . \"TENISEI~U\" ,",
"ref_id": null
},
{
"start": 176,
"end": 186,
"text": "\"TEOhLi\" ,",
"ref_id": null
},
{
"start": 187,
"end": 194,
"text": "\"SOKQ\\;",
"ref_id": null
},
{
"start": 195,
"end": 215,
"text": "Ri\" and \"TEII@2~U\" )",
"ref_id": null
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "Case: features of surface case(ex. \"Gd\"",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "\"I\u00a20\" \"NI' \"TO'. .... ),",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "modified relation~iu!!ui or ~B~o!t modification)",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "Conjunctive: sub-category of semantic feature(cause/reason, conditional/provisional, accompanyment, time/place, purpose, collateral, positive or negative conjunction, ere) _7.., Data Base St.r_u._c.tur_e Qf~_h_e Lex, icon",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "As this system uses LISP as the programming language, the lexicons are punched up as S-expressions and input to computer files (see Figure 3 ) . For the lexicon data base used for syntax analysis, only the lexical items are hold in main storage; syntactic and semantic features are stored in VSAM random acess files on disk(see The head character of the lexical unit is used as the record key for the hashing algorithm to generate the addresses in the VSAM files.",
"cite_spans": [],
"ref_spans": [
{
"start": 132,
"end": 142,
"text": "Figure 3 )",
"ref_id": null
}
],
"eq_spans": [],
"section": "Process of semantic marking",
"sec_num": "5.2"
},
{
"text": "We have reached the opinion that it is necessary to develop a way of allocating semantic markers automatically to overcome the ambiguities in word meaning confronting the human attempting this task.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "con__cJJ~i_o_n",
"sec_num": "8."
},
{
"text": "In the same thing, there are problems how to find an English term corresponding to the Japanese technical terms not stored in dictionary, how to collect a large number of technical terms effectively and to decide the length of compound words, and how to edit this lexicon data base easily, accurately, safely and speedily.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "con__cJJ~i_o_n",
"sec_num": "8."
},
{
"text": "In lexicon development for a huge volume of You(~n , it is quite important that we have a way of collecting automatically many usages of verbal case frames, and we suppose it exist different case frames in different domains.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "con__cJJ~i_o_n",
"sec_num": "8."
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],
"back_matter": [
{
"text": "We would like to thank Mrs. Mutsuko Kimura(IBS~, Toyo information Systems Co. Ltd., Japan Convention Sorvice Co. Ltd., and the other members of the Mu-projeet working group for the useful discussions which led to many of the ideas presented in this paper.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Ackn_o_Ki~Lgm~_",
"sec_num": null
}
],
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"FIGREF0": {
"text": ", ~)] I~. 10 m/sec. \"C .~....~,a~ -~ ~ ,5",
"type_str": "figure",
"uris": null,
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"FIGREF1": {
"text": "! .... Bho~_.k~___Dia_gr_am of Pro~ess___o..f [~s_c_rJ._b_in~Yerb_al .Case Frames_",
"type_str": "figure",
"uris": null,
"num": null
},
"FIGREF3": {
"text": "Figu~ 2, Sy.a_t~m__of",
"type_str": "figure",
"uris": null,
"num": null
},
"FIGREF4": {
"text": "~ ~) ($~Im~ SUB) ($~=-~' OF OH) C$~11~ 1)) (($~I~ I:) ($~%~ REC) ($~J~=--~\" xx) (S~4Ji~ 1))) (S~flt~ \u00a2$~,~ \".~t~\")))))",
"type_str": "figure",
"uris": null,
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},
"FIGREF5": {
"text": "Lexicon Data Base Structure for Analvsis",
"type_str": "figure",
"uris": null,
"num": null
},
"TABREF0": {
"text": "GOAl. PARtr,cu'. COl'~i,or~ent. CONdition. 9ANge ...... ..................................",
"type_str": "table",
"html": null,
"num": null,
"content": "<table><tr><td>TCil</td><td>consists</td><td>of</td><td>vet b.</td></tr><tr><td colspan=\"4\">~'~9ou _.s'hi ~adjec:tive and L<Cigo~!d()!#_mh~ adjectival</td></tr><tr><td colspan=\"4\">noun.. L~bkujo ,~hi include inner case and outer'</td></tr><tr><td colspan=\"4\">case markers in Japanese syntax. But a single</td></tr><tr><td colspan=\"3\">Iqol,'ujo ~/l; corresi:~ond.~ to several deep cases:</td><td>for</td></tr><tr><td colspan=\"4\">instance, \".\\'I\" indicates more than ten case labels</td></tr><tr><td colspan=\"4\">including SPAce. Sp~:ee TO. TIMe, ROl,e, MARu,-:I .</td></tr><tr><td colspan=\"4\">We analyze re]atioP,<; br:twu,::n [<~,kuj~, ,>hi anH cas,:,</td></tr><tr><td colspan=\"4\">labels and wr.i..i,c thcii~ out, manu~,l]y acc,.:,idii~, t,:,</td></tr><tr><td colspan=\"3\">the ex~_m,;:]e.s fotmd o;;t ill samr, te texts.</td><td/></tr></table>"
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"TABREF1": {
"text": "S~!tC~!--~jc i sh i ), action nouns 2 (others }.adverbial nouns. ~bk:\u00b1tio-shi-teki-i,~ishi (noun with case feature ~, ~l~:okuio-shi-teki-i~i~hi",
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"content": "<table><tr><td>4.</td><td colspan=\"4\">Sub-cat~or_ies</td><td>of</td><td colspan=\"2\">Parts</td><td>of SDeech</td></tr><tr><td colspan=\"8\">accordiDg to their Syntactic Features</td></tr><tr><td colspan=\"8\">The parts of speech are classified into 13</td></tr><tr><td colspan=\"3\">main categories:</td><td/><td/><td/><td/></tr><tr><td colspan=\"8\">nouns, pronouns, numerals, affixes, adverbs.</td></tr><tr><td>verbs.</td><td/><td colspan=\"4\">~eiy_ou--~h~.</td><td/><td>Ke~uoudou-shi.</td></tr><tr><td colspan=\"6\">Renlcli-shii~adnoun), conjunctions,</td><td/><td>auxiliary</td><td>verbs,</td></tr><tr><td colspan=\"6\">markers and ./o~shi(postpositional</td><td/><td>particles;.</td><td>Each</td></tr><tr><td>category</td><td>is</td><td colspan=\"3\">sub-classified</td><td colspan=\"3\">and divided into 56</td></tr><tr><td colspan=\"3\">sub-categories(see</td><td colspan=\"3\">Appendix A);</td><td colspan=\"2\">those which are</td></tr><tr><td>mainly</td><td colspan=\"2\">based</td><td>on</td><td colspan=\"2\">syntactic</td><td/><td>features,</td><td>and</td></tr><tr><td colspan=\"7\">additionally on semantic features.</td></tr><tr><td colspan=\"8\">For example, nouns are divided into</td><td>11</td></tr><tr><td colspan=\"8\">sub-categories; proper nouns, common nouns, action</td></tr><tr><td colspan=\"8\">nouns I ((noun</td></tr><tr><td>with</td><td colspan=\"3\">conjunction</td><td colspan=\"2\">feature),</td><td/><td>unknown</td><td>nouns,</td></tr><tr><td colspan=\"8\">mathematical expressions, special symbols</td><td>and</td></tr><tr><td colspan=\"8\">complementizers. Action nouns are classified into</td></tr><tr><td colspan=\"2\">,~lhc(~-mc'ishi</td><td>ia</td><td colspan=\"2\">noun</td><td colspan=\"2\">that</td><td>can</td><td>be</td><td>a</td></tr><tr><td colspan=\"4\">noun-plus-St~U,,doing></td><td colspan=\"4\">composite verb) and other</td></tr><tr><td colspan=\"8\">verbal nouns, because action noun ] is also used</td></tr><tr><td colspan=\"5\">as the word stem of a verb.</td><td/><td/></tr><tr><td>Other thau active voice</td><td/><td/><td/><td/><td/><td/></tr><tr><td>converted to active</td><td/><td/><td/><td/><td/><td/></tr><tr><td>. , [</td><td/><td/><td/><td/><td/><td/></tr><tr><td>~ephce kakarijo-sh~('~A'. / ' NOMISHIKA' , 'NO', 'NO')wit~ kaku~o-nhi</td><td/><td/><td/><td/><td/><td/></tr></table>"
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