| { |
| "paper_id": "C96-1023", |
| "header": { |
| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T12:51:25.089148Z" |
| }, |
| "title": "Classifiers in Japanese-to-English Machine Translation", |
| "authors": [ |
| { |
| "first": "Francis", |
| "middle": [], |
| "last": "Bond", |
| "suffix": "", |
| "affiliation": { |
| "laboratory": "", |
| "institution": "NTT Communication Science Laboratories", |
| "location": {} |
| }, |
| "email": "" |
| }, |
| { |
| "first": "Kentaro", |
| "middle": [], |
| "last": "Ogura", |
| "suffix": "", |
| "affiliation": { |
| "laboratory": "", |
| "institution": "NTT Communication Science Laboratories", |
| "location": {} |
| }, |
| "email": "" |
| }, |
| { |
| "first": "Satoru", |
| "middle": [], |
| "last": "Ikehara", |
| "suffix": "", |
| "affiliation": { |
| "laboratory": "", |
| "institution": "NTT Communication Science Laboratories", |
| "location": {} |
| }, |
| "email": "" |
| } |
| ], |
| "year": "", |
| "venue": null, |
| "identifiers": {}, |
| "abstract": "This l)a.i)cr t)rot)oses ;m mmlysis of classifters into ['our ma,jor l;yl)", |
| "pdf_parse": { |
| "paper_id": "C96-1023", |
| "_pdf_hash": "", |
| "abstract": [ |
| { |
| "text": "This l)a.i)cr t)rot)oses ;m mmlysis of classifters into ['our ma,jor l;yl)", |
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| "section": "Abstract", |
| "sec_num": null |
| } |
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| "body_text": [ |
| { |
| "text": "1 Introduction N()m~ I)hras(',s in Ja.pmms(' difl'(!r from l,hos(~ in l';nglish in two ilnt)orl;mll; ways. ]?irsl;, ,]al)ml(~s(! has no ('quivalent synl;a(:l;i(: (;a,l,('gory l; (/ l\",nglish (l(;t(',rtniners. S(;(;on([, thtu 'c is tit) grmmuatical tam'king of tl/lllil)(*,r, t ])~(~(;~l.ll,q(; ()f tlt(~SC diIl'(w(m(:es~ ml m('.ri(:a.1 expr(~ssi(/ns a.r (~ r('.aliz(;d very (lifft!r('.ntly in .la.lm, nes(~ and English. [n English, comltal) l(; nouns can ])t; directly m()dili(!d l)y a mun(!ral: 2 dog,s. In ,la,limmse , h()w(!v('.r, nmncrals (:a,nnot, (lire(:tly mo(tiily C(/llllllOtl llOllliS, inst('ml a (:lassitier is us(;(t, in l;he stunt; way l;h~d; ~t ])arl;il;ivc noun is used wil,h a,n unc(mnta.ble noun in English: 2 pieces of fltrnit',,r'e. In addition, when .]a.I)an(*a ~.", |
| "cite_spans": [ |
| { |
| "start": 178, |
| "end": 224, |
| "text": "(/ l\",nglish (l(;t(',rtniners. S(;(;on([, thtu", |
| "ref_id": null |
| }, |
| { |
| "start": 354, |
| "end": 440, |
| "text": "(~ r('.aliz(;d very (lifft!r('.ntly in .la.lm, nes(~ and English. [n English, comltal)", |
| "ref_id": null |
| } |
| ], |
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| { |
| "text": "is translated int(/li;nglish, tim scle(:tion ()I' a,l/pr()t)ria, l;(', d(;t(,,rmin(;rs, su(:h sis re'tit;los a,n(t t)ossc.ssiv(~ l/rOnouns, tLtl(t l;h(', d(;1,('amin~l;i(nt (if (:()unta.t)ilit;y a.nd mmfl)(;r is l)r()l)l('ma.tic.", |
| "cite_spans": [], |
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| { |
| "text": "Various s(/lutions to t;he pr(/I)h~ms ()f gen(wating a.rti(:l(',s ;rod t)oss(',ssiv(~ 1)ronouns a.nd (t(;t('~rmining (:omltal)ilil;y a.nd munbcr have be(',n I/r()t)oseA (MunLta and Nagao, 1993; Cornish, Fujit; % and Sugimura, 1994; ll(md, Ogm'a, and Kawaoka ., 1!)95). The (tiff(~r('.n(',('.s t) cl,w(wal the way mun(',ri-(:M Cxlirt',ssi(/ns are realized in ,la.t)all(!s(~ a.ud English lists 1)Cell lo, ss studi (', d (Asa.hioka, llira.knwa, &n(l Alll; l, tl(), 1.990) . In this 1)a.t)(;r we l)roI)()s(~ m~ mmlysis of (:lassifiers based on lirOl)('rties of l)oth ,lapan(~,q('. mM English. Our caLegory (If classitier includes both ,]a.im,nesc josusM 'tmm (.q'al clas-. ~.lal)mW~se does noI, ]ta,ve contrasting singular and l)hlr;fl forms of nouns. silicrs' mM English lmr(;itivo, nouns. W(', divide classifiers inl;o four m~ki(ir l,yl)c.s: UNIT, METIll(:, (;l/()[Jl' ~-Llld S['E(JII,;S. UNIT (:lassiIio.rs are I'urtlmr divided inl,o (II,;NEIIAI,, TYPI(?AI, ~LII(I SI'I,;(:IAI., whil(~ MI,YI'I/I(? classifiers are divided into h,ll,;:\\StJl\u00a2l,; ~/,lld (R)NTAINEII. classifiers. All,hough our ~malysis was tmscd on l;hc characteristics of, and difl'o, rences lmtwt!en, .bq)ane,q(! and Euglish, we fomtd il; t;o }m strikingly similaa to the, annlysis for Thai 1)rol)OS (~d by Sornlcrtlamwmic, het al. (1994) , which sugg(',sts I;ha.l, Lhe re,quits ma.y bc useful for e.xa.miniug ol;hcr la.ngllages.", |
| "cite_spans": [ |
| { |
| "start": 169, |
| "end": 193, |
| "text": "(MunLta and Nagao, 1993;", |
| "ref_id": null |
| }, |
| { |
| "start": 194, |
| "end": 209, |
| "text": "Cornish, Fujit;", |
| "ref_id": null |
| }, |
| { |
| "start": 210, |
| "end": 231, |
| "text": "% and Sugimura, 1994;", |
| "ref_id": "BIBREF6" |
| }, |
| { |
| "start": 232, |
| "end": 257, |
| "text": "ll(md, Ogm'a, and Kawaoka", |
| "ref_id": null |
| }, |
| { |
| "start": 269, |
| "end": 295, |
| "text": "The (tiff(~r('.n(',('.s t)", |
| "ref_id": null |
| }, |
| { |
| "start": 412, |
| "end": 415, |
| "text": "(',", |
| "ref_id": null |
| }, |
| { |
| "start": 416, |
| "end": 429, |
| "text": "d (Asa.hioka,", |
| "ref_id": null |
| }, |
| { |
| "start": 430, |
| "end": 441, |
| "text": "llira.knwa,", |
| "ref_id": null |
| }, |
| { |
| "start": 442, |
| "end": 452, |
| "text": "&n(l Alll;", |
| "ref_id": null |
| }, |
| { |
| "start": 453, |
| "end": 455, |
| "text": "l,", |
| "ref_id": null |
| }, |
| { |
| "start": 456, |
| "end": 461, |
| "text": "tl(),", |
| "ref_id": null |
| }, |
| { |
| "start": 462, |
| "end": 468, |
| "text": "1.990)", |
| "ref_id": null |
| }, |
| { |
| "start": 655, |
| "end": 668, |
| "text": "(.q'al clas-.", |
| "ref_id": null |
| }, |
| { |
| "start": 1265, |
| "end": 1303, |
| "text": "(~d by Sornlcrtlamwmic, het al. (1994)", |
| "ref_id": null |
| } |
| ], |
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| { |
| "text": "The analysis inl;rotlut;ed in this tin.per has })eun iml)lem(!nla',(l in NTT Commutfi(:al;i(m S(:ien(:c l,a.1)or;~tori('.s' .J;qm.n(~s(>t()-English nmchitm tr;mslal;i(m system ALT-J/E (lko, lm.r;~ el, al., 1!)91;", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "", |
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| { |
| "text": "()gm'a ut al., 1993) ,qnc(! 1994. Ex~mlt)les o1' how it, has l)c(~n inipl(un(!nlx~(1 in ALT-J/E m(~ w(/v(!n l, hrough()ut the l;(!x[;, nlth(mgh tim analysis it;self is not ti(',(1 t;o any t'ornmli,qm or ])ml;it:ulm repr(> scnl;a,l;ion, so is ;Ma,ptat)lt: to any sysl;t;m, We Sl;al'l; O[[ l)y (!xmnining re(rot/lingual mm.ly ses o[ ,laIm.no, s(~ classiticrs and English pm'l,it;ivt,, (!Xl)l't~SSit)llS (Sccl:ion 2). Then we introduce ore bilingual mmlysis o1 classifiers a,nd show how this a.na]ysis can lm used in a..la.pmms(:-l:()-lC, nglish mn- (:hin(~ trm>lal, i(m sysI, em (Se(; l; i(m 3) . We ~lls() ex-;Llltill(! II!.()l'(~ (',Olllpl(~,X (',aS(!S who, l'C (;lassi/i(ws are used liD; normal nouns (S(w, ti(m 4). Flintily we (:Omllarc ore mmlyMs 1,() oth(;r l)(~ol)le's (S(w.l;i()n 5).", |
| "cite_spans": [ |
| { |
| "start": 547, |
| "end": 563, |
| "text": "(:hin(~ trm>lal,", |
| "ref_id": null |
| }, |
| { |
| "start": 564, |
| "end": 573, |
| "text": "i(m sysI,", |
| "ref_id": null |
| }, |
| { |
| "start": 574, |
| "end": 582, |
| "text": "em (Se(;", |
| "ref_id": null |
| }, |
| { |
| "start": 583, |
| "end": 585, |
| "text": "l;", |
| "ref_id": null |
| }, |
| { |
| "start": 586, |
| "end": 592, |
| "text": "i(m 3)", |
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| { |
| "text": "Thr(/ughout the, pallor we us(; th('. following al)ln'(;viations: A, B (/r N: z,oun or noun t)hrase; C: cla~sifi(;r, X: Nmneral, with ,]apa.n('.s('. in it;ali(:s. The resulting numeral-classifier noun phrase can modify another noun phrase, either linked by no 'of ' 'XC-no-N', or 'floating' elsewhere in the sentence, typically directly after the noun phrase it modifies 'NXC'. It can also occur on its own, with anaphoric or deictic reference. Asahioka, Hirakawa, and Amano (1990) identify seven different patterns of use. In order to concentrate on the translation of classifiers and number, we will restrict our discussion to noun phrases of the type 'XC-no-N' and not discuss the problems of resolving anaphoric reference and floating quantifiers.", |
| "cite_spans": [ |
| { |
| "start": 264, |
| "end": 300, |
| "text": "' 'XC-no-N', or 'floating' elsewhere", |
| "ref_id": null |
| }, |
| { |
| "start": 445, |
| "end": 481, |
| "text": "Asahioka, Hirakawa, and Amano (1990)", |
| "ref_id": "BIBREF2" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "", |
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| }, |
| { |
| "text": "Semantically, each classifier relates to a class of nouns (Kuno, 1973, 25) , often fairly arbitrarily. For example -hiki '(small) animal' is used to count small animals excluding rabbits, which are counted with -wa 'bird'. There is a default classifier -tsu 'piece' which can be used to count almost anything.", |
| "cite_spans": [ |
| { |
| "start": 58, |
| "end": 74, |
| "text": "(Kuno, 1973, 25)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Monolingual Analyses of Classifiers", |
| "sec_num": "2" |
| }, |
| { |
| "text": "In English, numerals can directly modify countable nouns 'X N'. In order to enumerate uncountable nouns, either the uncountable nouns have to be reclassified as countable nouns, or embedded in a partitive construction: two beers or two cans of beer 'X N' or 'X C of N' (Quirk et al., 1985, 249 ). This partitive construction is similar to the Japanese quantifying construction 'XC-no-N'. Quirk et al. (1985, 249-51) divide partitive nouns into three main categories QUALITY PAR-TITIVES, QUANTITY PARTITIVES, and MEASURE PARTITIVES. QUANTITY PARTITIVES are further divided into three cases, the first where the embedded noun phrase is uncountable, the second where it is plural, and the third where it is singular and countable. All the partitive nouns themselves are fully countable.", |
| "cite_spans": [ |
| { |
| "start": 269, |
| "end": 293, |
| "text": "(Quirk et al., 1985, 249", |
| "ref_id": null |
| }, |
| { |
| "start": 388, |
| "end": 415, |
| "text": "Quirk et al. (1985, 249-51)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "English 'Classifiers'", |
| "sec_num": "2.2" |
| }, |
| { |
| "text": "QUANTITY PARTITIVES where the embedded noun phrase is headed by an uncountable noun, the first case, are then divided into GENERAL PAR-TITIVES such as piece which serve only to quantify and TYPICAL PARTITIVES such as grain which are more descriptive.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "English 'Classifiers'", |
| "sec_num": "2.2" |
| }, |
| { |
| "text": "2There are some examples of words that can be either a common noun or josftshi: for example gy5 'line' or hako 'box', which can follow a numeral or stand alone. These nouns can be handled in two ways: (a) as a lexical class that combines the properties of common nouns and josftshi, or (b) as two separate lexical entities. ALT-J/E follows option (b), such nouns are entered into the lexicon twice, once as a common noun and once as a jos~ishi.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "English 'Classifiers'", |
| "sec_num": "2.2" |
| }, |
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| "text": "As there is no direct fit between English and Japanese, it is necessary to categorize the Japanese and English classifiers and to define rules which will enable effective machine translation. We divide classifiers into four major types: IIN]T (Section 3.1), METRIC (Section 3.2), GROUP (Section 3.3) and SPECIES (Section 3.4). The main criteria for the analysis are the restrictions placed, in English, on the countability and number of the embedded noun phrase in a partitive construction. Whether a noun is a classifier, and if so which type, is marked in the lexicon for each Japanese/English noun pair. We distinguish between five major different noun countability preferences, based on the analysis of Allan (1980) , adapted for use in machine translation by Bond, Ogura, and lkehara (1994) . 'Fully countable' nouns, such as knife, have both singular and plural forms, and cannot be used with determiners such as much. 'Uncountable' nouns, such as furniture, have no plural form, and can be used with much. Between these two extremes are nouns such as cake, which can be used in both countable and uncountable noun phrases. They have both singular and plural forms, and can also be used with much. We divide such nouns into two groups: 'strongly countable', those that are more often used to refer to discrete entities, such as cake, and 'weakly countable', those that are more often used to refer to unbounded referents, such as beer. The fifth major type of countability preference is 'pluralia tanta': nouns that only have a plural form, such as scissors.", |
| "cite_spans": [ |
| { |
| "start": 707, |
| "end": 719, |
| "text": "Allan (1980)", |
| "ref_id": null |
| }, |
| { |
| "start": 764, |
| "end": 795, |
| "text": "Bond, Ogura, and lkehara (1994)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "A Bilingual Analysis of classifiers", |
| "sec_num": "3" |
| }, |
| { |
| "text": "UNIT classifiers are the prototypical classifiers. A UNIT classifier will be realized in Japanese a~ a jos{shi. However, there are three possible translations of a Japanese noun phrase of the form ~XCno-N', where C is a unit classifier: Individuate: Translate as 'X N', where the classifier C is not translated and the numeral directly modifies the countable English noun phrase: 1-hiki-no-inu 'l-piece of dog' --+ 1 dog.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Unit classifiers", |
| "sec_num": "3.1" |
| }, |
| { |
| "text": "Part: Translate as 'X C of N', where the classifier is translated by its translation equivalent (from the transfer dictionary) and N is uncountable (headed by a bare singular noun): 1-tsubu-no-kome 'l-grain of rice' -+ 1 'grain of rice.", |
| "cite_spans": [], |
| "ref_spans": [], |
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| "section": "Unit classifiers", |
| "sec_num": "3.1" |
| }, |
| { |
| "text": "Default: Translate as 'X C of N' where the classifier is replaced by a default that depends on the embedded noun and N is uncountable. The default is normally piece, but this can be over-ridden by an explicit entry for N's default classifier in the lexicon: The translation of classifiers is complicated by the fact that classifiers and their relationships to nouns are both arbitrary and language dependent. Consider the Japanese classifier -mai 'sheet', which is used for counting fiat objects. This has no direct English equivalent. As a default, it is entered in the dictionary as a GI.'NEI{AL classifier with the translation piece. There are however several fiat, objects for which piece is inappropriate in English: food-stuffs (slice); paper, glass, cloth and leather (sheet); bacon (rasher); and financial contracts (contract). The selection of an appropriate translation is not dependent on this analysis and can be left, to the normal machine translation process. In ALT-J/E it is done by examining the semantic category of the embed-aIf N's countability preference is pluralia tanta then N will never be individuatcd. If N is parted or defaulted there axe two possibilities: either, if the dictionary entry for N has the default classifier pair then it will be used as the classifier or, if N has no default classifier, then a different translation is searched for in the dictionary and used instead. If there is no nonpluralia tanta translation equivalent, then the translation will default to 'X C of N' as above, but with N headed by a bare plural noun. ded noun. Once an appropriate translation of the classifier has been found, knowledge of its type allows the system to decide the appropriate form of the final translation.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Unit classifiers", |
| "sec_num": "3.1" |
| }, |
| { |
| "text": "The next overall category is METRI() classifiers:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Metric classifiers", |
| "sec_num": "3.2" |
| }, |
| { |
| "text": "A noull phrase of the form 'XC-no-N', where C is a METRI(; classifier will be translated as 'X C of N', where N will be plural if it is headed by a fully countable or pluralia tanta noun. We fllrther subdivide METI/,IC classifiers depending on whether the resulting English noun phrase will have singular verb agreement (MEASURI'; classifiers), or plural verb agreement (CONTAINFat classifiers) as its default.", |
| "cite_spans": [ |
| { |
| "start": 27, |
| "end": 37, |
| "text": "'XC-no-N',", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Metric classifiers", |
| "sec_num": "3.2" |
| }, |
| { |
| "text": "(4) 2-kg-no-kami-ha jgbun da '2 kg of paper-TOP enough is' -~ 2 kg of paper is enough (5) 2-hako-no-kami-ha jubun da '2 box of paper-TOP enough is' -+ 2 boxes of paper\" are enough", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Metric classifiers", |
| "sec_num": "3.2" |
| }, |
| { |
| "text": "In fact both (4) and (5) could be translated with singular or plural verb agreement. The differentiation into MEASURE and CONTAINER provides a graceful default. Examples are given in Table 2 .", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 183, |
| "end": 190, |
| "text": "Table 2", |
| "ref_id": "TABREF2" |
| } |
| ], |
| "eq_spans": [], |
| "section": "Metric classifiers", |
| "sec_num": "3.2" |
| }, |
| { |
| "text": "GROUP classifiers combine with plural or uncountable noun phrases to make a countable noun phrase representing a group or set. A noun phrase of the form 'XC-no-N', where C is a GROUP classifier will be translated as 'X C of N', where N will be plural if it is headed by a fully or strongly countable noun or a pluralia tanta. Noun phrases of the form 'N-no-C', where C is a GROUP classifier (but not a jos~shi) will also be translated as 'C of N' where N will be plural if it is headed by a fully or strongly countable noun or a pluralia tanta. This allows us to give a uniform treatment of noun phrases such as (6) and (7) during English generation, even though their Japanese structure is very different. (6) 2-hako-no-pen '2 box of pen' 2 boxes of pens 'XC-no-N' (7) pen-no-hako 'box of pen' a box of pens 'N-no-C' Whether a notln is a GIll)UP classifier or not carl also be used to help determine the Irtlmber of ascriptive and appositive noun phrases. For example, in ALT-J/E the countability and number of two at)positive noun phrases are made to match each other, unless one element is plural and the other is a GI{OUP classifier. For example, many insects, a whole swarm, ... as opposed to many insects, bees I think, ... (Bond, Ogura, and Kawaoka, 1995) . Examples of (;Rein, classifiers are given in Table 3 .", |
| "cite_spans": [ |
| { |
| "start": 756, |
| "end": 765, |
| "text": "'XC-no-N'", |
| "ref_id": null |
| }, |
| { |
| "start": 1230, |
| "end": 1262, |
| "text": "(Bond, Ogura, and Kawaoka, 1995)", |
| "ref_id": "BIBREF5" |
| } |
| ], |
| "ref_spans": [ |
| { |
| "start": 1310, |
| "end": 1317, |
| "text": "Table 3", |
| "ref_id": "TABREF3" |
| } |
| ], |
| "eq_spans": [], |
| "section": "Group classifiers", |
| "sec_num": "3.3" |
| }, |
| { |
| "text": "The last type of classifier is sP,,;cn,;s classifiers. SI'ECII:S classifiers are partitives of quality and (;an occur with countable or uneo,lnt&ble llOlln phrases. The embedded noun phr~se will agree in number with the head noun phrase if flflly or strongly countable: a kind of car, 2 kinds of cars; a kind of equipment, 2 kinds of equipment. Exalnples of SPE(:mS classifier's are given in Table 3 .", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 392, |
| "end": 399, |
| "text": "Table 3", |
| "ref_id": "TABREF3" |
| } |
| ], |
| "eq_spans": [], |
| "section": "Speeies classifiers", |
| "sec_num": "3.4" |
| }, |
| { |
| "text": "When is a Classifier a Classifier?", |
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| "ref_spans": [], |
| "eq_spans": [], |
| "section": "4", |
| "sec_num": null |
| }, |
| { |
| "text": "In the analysis given above for Japanese noun phrases of the form 'XC-no-N', we have given no consideration 1;o the denotation of N, except for when choosing the at)propi'iate translation for C. Thus we assume that 'XC~no-N' will be translated as 'X C of N' or just 'X N' if N is countable, as in (8) or (9). However if N is a noun that denotes an attribute, such as PRICE or WEIGIIT, then the translation process becomes more complicated. In the simplest case the noun phrase 'XC-no-N' should be. translated as though the classifier' were a norreal noun, giving 'the N of X C', for examph'. (10), (ll). In other words, if N has the attribute AMOUNT then the noun phrase should normally be translated as though C were not a classifier. The interpretation of C is, however, ambiguous. C could be used as a elassiiier with the amount N in its scope (12), or C could have anaphoric reference (13). ALT-J/E chooses the interpret~tion shown in example (13) as its defmflt. Further, when N is an attribute and C measures the same attribute, the interpretation is again different. N)r exainple, if C measures N's attribute then the resulting noun phrase will be indefinite by default: a height of lore or a price of 10 yen. Ilowever if the noun phrase is used ascriptively then it; should be converted (;ither to an adjective it is lore high or a prel)osit;ional pin'as(; it is lO yen in price. Finally, if a noun phrase of this type is used to modify at]other noun then it line(is to lm converted to an adjective a .lOre high building or a post modifying prepositional phrase a chocolate 10 yen in price.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "4", |
| "sec_num": null |
| }, |
| { |
| "text": "The coml)inatio]ls of nouns and classifiers mentioned above can all be translated by the machine translation systerit ALT-J/E using the analysis of classifiers presented in this paper ill combination with a semantic hierarchy of 2,800 categories common to all nouns, as described in Ikeharaetal. (1991) .", |
| "cite_spans": [ |
| { |
| "start": 270, |
| "end": 302, |
| "text": "described in Ikeharaetal. (1991)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "4", |
| "sec_num": null |
| }, |
| { |
| "text": "The particle no 'of', has many possible interpretations, Shimazu, Naito, and Nomura (1987) identify tire main types of A-'n.o-]l expressions, and some 80", |
| "cite_spans": [ |
| { |
| "start": 57, |
| "end": 90, |
| "text": "Shimazu, Naito, and Nomura (1987)", |
| "ref_id": "BIBREF16" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "4", |
| "sec_num": null |
| }, |
| { |
| "text": "We summm.'iz(~ our m~alysis of classifiers in Table d. Our aualysis was based mainly (m I;h<! I)rot)eri;ies of Lhe g<;n(',rat;<',(1 li;nglish, so ix naturally (luilx~ (:lose t,o I;he division ()f t)arl;i@v(! nouns propose<l by Quirk el; al. (1985) . The analysis is also (tuil;e, (:lose to those t)roi)ose([ by Kamei and Muraki (1995) for Jal)ancsc and S()IIIleri;lmnwufi(:h el; al. (1994) f()r Thai. This supports Allah'S (1977) ass('a'l:io,l t;hat; \"diverse language eOlnlnunil, i(~s (:ateg/orize. 1)er(:eived phenom--(',ha in similar ways\". The <lit['erenl; analyses are (:oml)ar (', d in Tabh', 5. We make th('. distinct, ion b(',l;we(m <:lassitiers of frequen<:y and ol;her UNIT (:lassitiers })y u,qing our general sema.nl;i(: hi<~rarchy. Sornlerl;lamwmi(:h el; M.'s VEHBAI, (:lassiti(;rs \"ally (:lassifier whi{:h is derived from a verb [...1 /kraa(l haa muan/ 'five roils of pal)er'.\"", |
| "cite_spans": [ |
| { |
| "start": 227, |
| "end": 236, |
| "text": "Quirk el;", |
| "ref_id": null |
| }, |
| { |
| "start": 237, |
| "end": 247, |
| "text": "al. (1985)", |
| "ref_id": "BIBREF15" |
| }, |
| { |
| "start": 311, |
| "end": 334, |
| "text": "Kamei and Muraki (1995)", |
| "ref_id": "BIBREF9" |
| }, |
| { |
| "start": 583, |
| "end": 586, |
| "text": "(',", |
| "ref_id": null |
| }, |
| { |
| "start": 587, |
| "end": 598, |
| "text": "d in Tabh',", |
| "ref_id": null |
| }, |
| { |
| "start": 599, |
| "end": 601, |
| "text": "5.", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Comparisons with other Analyses", |
| "sec_num": null |
| }, |
| { |
| "text": "(:an be in(:lu<h',d in the METRIC (:a.t;egory, ;dr;hough il; may })e t;he (:ase l;hal; l;hey have a diflhrenl; parl; of sl)ee(:h in Thai. Kamei and Muraki (1995) put UNIT (:lassitiers inl;o {;wo (:lasses: 'Counl;ing T()l;aJ Amomtl;': 3kg of su.(tar' and ~Coull.Ling; all Al;t;ril>lll;e Yahte': a .spc.ed of (iOmph. ']'his disl:in(:l;ion t)elongs I;o l;he inW, rt)ret, ation ol' (;he (:lassitier in (:ontx~xt, rat;h<~r than il;s hdw, l'(!nt prOl)erl;ies , so we fe(!l t:he distin(:l,ion sh(mh[ l)e made ([llI'illg l>ro<:essint,~, as (h> s(:ril)ed in Se(-1,ion d, val,her t;ha.n its l)arl, oJ t,he analysis <)f l,he (:lassiti<'.rs t;hems(~lv<~s.", |
| "cite_spans": [ |
| { |
| "start": 138, |
| "end": 161, |
| "text": "Kamei and Muraki (1995)", |
| "ref_id": "BIBREF9" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Comparisons with other Analyses", |
| "sec_num": null |
| }, |
| { |
| "text": "In this im,l)er we pres,:ull; a,n analysis off (:lassitieT~, suii;al)le for use ill a .]apanese-to-ldnglish ma<:hin<~ I, ranslal;ion sysl,('m. We divide (:lassitiers into four Furl;h('J\" work remains 1;() be done in (',xmnining the <listribul;ion of classifiers in differ(;nt, domains, and possibly identit~ying classifiers a.ul,omal;i<:a,lly.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Conclusion", |
| "sec_num": "6" |
| } |
| ], |
| "back_matter": [ |
| { |
| "text": "Pie(:e Unit, ; Si;(',<:i~ -Q uanl.|l;y/l'yl)l(. ", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "annex", |
| "sec_num": null |
| } |
| ], |
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| "FIGREF0": { |
| "uris": null, |
| "text": "1-pal-no mizu 'l-cup of water' --> 1 e?Lp of wate\u00b0f (CONTAINFI/.) (9) i-tsu-no koppu 'l-piece of cup' --+ 1 C~tp (GENEI/AI,)", |
| "type_str": "figure", |
| "num": null |
| }, |
| "FIGREF1": { |
| "uris": null, |
| "text": "(10) 1-pal-no nedan 'l-cup of price' the price of lcv, p (11) 1-tsu-no ncda'n [-ha lOen da] 'l-piece of t)riee [-'cop 1(] yen is]' -> the price of 1 (thing) fis 10 yen]", |
| "type_str": "figure", |
| "num": null |
| }, |
| "FIGREF2": { |
| "uris": null, |
| "text": "12) 1-sh'ili-no 'n, edan '1 kind of price' -~ 1 kind of price (13) 1-st]u-no neda'n, '1 kind of price' -~ th.e price of .l kind/of something]", |
| "type_str": "figure", |
| "num": null |
| }, |
| "FIGREF3": { |
| "uris": null, |
| "text": "ma,ior tyl)es: UNIT, METI/.IC~ (~l/.()Ul) /Hid SI)},',CII,;S. IJNIT classifiers arc, further divided inl;o (IIqNEI{.AI,~ TYI'ICAI, ;I,II(l SI'E(:IAI,, whil(; METI{IC (;]assitiers are divided iltl;o MEASUI/.I,; all([ CONTAINEI{ (:]ilssifters. The analysis ix 1)ased on <:ha.ra.<:lx~risl;i(:s 1)e<'uliar 1;o Japanese mM English, a.s well as i,h(', differences bel;we(m I;hem. The resuli;ing amtlysis ix shown {;<> }>e similar t;o ()n(~ pr()pose(t tbr Thai, an unrelaJ;(xl laJtguage, suggesl:iug thai, it may I)e more widely al)pli(:al)le. The az|Mysis has }>e(!n imt)lemen(x~d in NTT's ,/at)a.nes<>lx)-English machine (,ranslal;ion syst;(;m AL'.r-J/E si~<:(,. 19.()4.11; makes 1)ossible a uniform an(l st;raigh(;forwa.rd l;re~-tt, m(:nL of n()un phrases headed t)y classifiers.", |
| "type_str": "figure", |
| "num": null |
| }, |
| "TABREF1": { |
| "text": "Unit Classifiers", |
| "type_str": "table", |
| "content": "<table><tr><td>Noun Type</td><td>General</td><td>Typical</td><td>Special</td></tr><tr><td>Fully Countable</td><td>1 (log</td><td>1 dog</td><td>1 slice of dog</td></tr><tr><td>Strongly Countable</td><td>1 cake</td><td>1 crumb of cake</td><td>1 slice of cake</td></tr><tr><td>Weakly Countable</td><td>1 hair</td><td>1 strand of hair</td><td>1 slice of hair</td></tr><tr><td>Uncountable</td><td>1 piece of information</td><td>1 grain of information</td><td>1 slice of information</td></tr><tr><td>Pluralia Tanta (pair)</td><td>1 pair of scissors</td><td>1 pair of scissors</td><td/></tr><tr><td colspan=\"2\">1-tsu-no-kagu 'l-piece of furniture'</td><td/><td/></tr><tr><td>-~ 1 piece of furniture.</td><td/><td/><td/></tr><tr><td colspan=\"2\">The three types of UNIT classifier are summa-</td><td/><td/></tr><tr><td>rized in Table 1. a</td><td/><td/><td/></tr><tr><td colspan=\"2\">Having established three possible translations</td><td/><td/></tr><tr><td colspan=\"2\">of the 'XC-no-N' construction, we can proceed to</td><td/><td/></tr><tr><td/><td>not be</td><td/><td/></tr><tr><td colspan=\"2\">translated (individuate), otherwise the classifier is</td><td/><td/></tr><tr><td colspan=\"2\">translated (part). The final type of classifier, SPE-</td><td/><td/></tr><tr><td colspan=\"2\">CIAl,, is rare: classifiers which force an uncount-</td><td/><td/></tr><tr><td colspan=\"2\">able interpretation of even countable nouns, for</td><td/><td/></tr></table>", |
| "num": null, |
| "html": null |
| }, |
| "TABREF2": { |
| "text": "Container and Measure Classifiers Noun TypeContainer", |
| "type_str": "table", |
| "content": "<table><tr><td>Measure</td></tr></table>", |
| "num": null, |
| "html": null |
| }, |
| "TABREF3": { |
| "text": "Group and Species Classifiers", |
| "type_str": "table", |
| "content": "<table><tr><td>Noun Type</td><td>Group</td><td>Species (Si)</td><td>Species (Pl)</td></tr><tr><td>lqflly Countable</td><td>1 set of dogs</td><td>1. kind of dog</td><td>2 kinds of clogs</td></tr><tr><td>Strongly Countable</td><td>1 set of cakes</td><td>1 kind of c}~ke</td><td>2 kinds of cakes</td></tr><tr><td>Weakly Countable</td><td>l set of beer</td><td>1 kind of beer</td><td>2 kinds of beer</td></tr><tr><td>Uncountable</td><td>1 set of information</td><td>1. kind of infbrmation</td><td>2 kinds of informal;ion</td></tr><tr><td>Pluralia Tanta</td><td>1 set of scissors</td><td>1 kind of scissors</td><td>2 kinds of scissors</td></tr></table>", |
| "num": null, |
| "html": null |
| } |
| } |
| } |
| } |
