| { | |
| "paper_id": "C94-1003", | |
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| "date_generated": "2023-01-19T12:49:27.349525Z" | |
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| "abstract": "Distinguishing exceptional translation examples is an important issue in example-based transflw systems, because such systems use exceptional and general translation examples unifi)rmly. This l);qmr ,lescribes a mechanism for dealing with exc,q)tiomd translation examples in our example-hosed tnLnsfer system, Sim~lban, and proposes a method for identifying such examples in a translation exampl~base.", | |
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| "text": "Distinguishing exceptional translation examples is an important issue in example-based transflw systems, because such systems use exceptional and general translation examples unifi)rmly. This l);qmr ,lescribes a mechanism for dealing with exc,q)tiomd translation examples in our example-hosed tnLnsfer system, Sim~lban, and proposes a method for identifying such examples in a translation exampl~base.", | |
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| "text": "and that we are given the folh)wing Japanese input s(,~.tence (sl):", | |
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| "section": "Introduction", | |
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| "text": "(sl) watashi(l)ha de,,t~ku(cah'ulator) w,, shiy-OIISH rll.", | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
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| "text": "In the almve exami,h~s , (s l) in likely to Im more similar to (,,1) than (e2), b,~c~use the three Japanese verbs \"kyouyotmuru~\" \"tsakan,\" and \"shiyousuru\" are all w~ry simih~r, ~ and \"dent~ku\" (\"calculator\") is more similar to \"konl)yuutaa\" (\"computer\") than \"kurum~'?' (\"car\"). If this is the case, the English output ohtained by using (el) is (tl),'-' whereas it should he 0,2):", | |
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| "section": "Introduction", | |
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| "text": "In recent years~ the example-based approach ha.s been used in many areas of natural language l)mcessing [3, 7, 8, 10~ 9, 1] . We haw~ been tlsing this al)proach to develop a transfer system called 5'imTra', [13, 14, 16] . However, a bottleneck occured in the collection of large numbers of translathm examples consisting of pairs of parsed structures in the source and target languages (hereafter we (:all these structures translation patterns)~ because parsing is not a perfi~et process. We now have some methods for overcoming this problem. For instance, recent studies [2, 11, 6, 12] have proposed mechanisms for collecting pairs of parsed structures automatically from translation examples, and in the previous paper [15] , 1 proposed ,~ method for extracting relevant translation patterns by comparing a wrong translation resttlL and its correct translation. Using these methods, we ca.n now collect translation patterns reh~tively easily.", | |
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| "text": "[3, 7, 8, 10~ 9, 1]", | |
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| "text": "There is, however, another problem ca.lled e~:ample inte,\u00a2e,~nce, wl,ich means that an ,xceptional (or id iomatie) translation pattern is selected when a general translation pattern should be selected; this has t~ side-effect on the construction of a target structure. Suppose that we have the following two translation examples from Japanese to English (el) and (e2), I share the use of ~ computer.", | |
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| "text": "(e2) watashi(I) ha~ kurum~(ear) wo tsnkau.", | |
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| { | |
| "text": "]\" /ISe a. car.", | |
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| "section": "Introduction", | |
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| "text": "(tl) I use the use of a calculator.", | |
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| "text": "(t2) I use a calculator.", | |
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| "text": "This probh~nl occurs because examph'~-ba,sed transfer systems choose examples simply on the basis of similarity. This ca.n be considered by using the analogy of cells like those shown in Figure 1 . In the [igure, a dot represents a translation e\u00d7aml)le ~ and a cell represents a spac(! in which an input is determined to be similar. According to this analogy, all example-blused system chex:ks the cell in which an input is located, ;~nd uses an ex~mple gow~rning the cell. If a new exa.mt)le is added in this space, it cell for it is created as if cell division. If an input happens to fall into the cell of an exceptional example, it is wrongly tr~mslated. Ther,d'ore~ an exce.ptitmal example shoukl be added as ~ spechd cell (a shaded dot in Figure 1 ) that h~us no exte,t in the example-based space, so that it. cannot he used unless it matches the input exactly. Thus, an examl~le-based transfer system must deal with ,~xctq)tiomd translation patterns st:parately when calcuhtting similarity.", | |
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| "start": 187, | |
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| "text": "Figure 1", | |
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| "text": "Figure 1", | |
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| "text": "This paper describes a mechanism used in Sim~lFan for dealing with exceptional translation patterns in the same framework as general translation patterns, and proposes a method for identifying exceptional tnrnsh~tion patterns in ~ tr~ulsla.tion pattern base.", | |
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| "text": "The next section describes a mechanism for dealing with such translatimL patter.s, and Section 3 de-1 Actually, they are in the same c~ttegory (or the same lmff) in the JItpttll~!Se thestmrus lh nr i-Go-l[you [5] . r['h[~ Illltill Vftl'll iS /:llltllgl!\u00a2l fl'tllll \"shltrt!\" to IU4t :\" ]leCallSly \"share\" is not ~t transh~tiou of \"shiyousuru.\" where bghcode(w ) is the code vMue in the Bunrui-Goi-Hyou, bghma:c is the maximal difference of the bghcodes, and 6 is a penalty value incurred when wl and w2 are not identical. This equation is used for lexical-forms in general translation patterns. If one is a lexicM-form which requires exact-match in an exceptional translation pattern, then the distance is calculated as follows: 0 wl is identical to w 2 distance(wl, w2) 1 othevwlse", | |
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| "text": "[5]", | |
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| "text": "aBunrui-Goi-IIyou is a Japanese thesaurus consisting of large trees for nominals, adjectives, and verbs. Each node is assigned a unique nmnber. Similar concept words are locattxl in similar positions (or assigned similar numbers) in these trees.", | |
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| "text": "A lexical-forni has a distinctive fea.tnre that makes it possible to determine which equation should be used hi cMculating similarity I if one of two le.xlcal-forms is expressed by a single-quoted string, then the distance between the lexical-forms is calculated by using the second equation; on the other hand, if both lexicalforms are expressed by double-quoted strings, then their distance is calc:nlated by using the first equation.", | |
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| "text": "Thus, an exceptional translation pattern is distinguished by having nodes whose lexicM-forrns are single-quoted strings in its source part, while a general translation pattern is distinguished by having nodes whose lexicM-fi~rms are all double-quoted strings in its source part.", | |
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| "text": "Not MI nodes in the source part of an exceptional translation pattern are necessarily single-quoted strings; single-quoted string nodes and don bh+-quoted string nodes may be mixecl in a translation pattern, ht Figure 2 , (tpl) is an exceptional tr;ulslation pattern and (tp2) is a general translation pattern. Note tt~tt the root node of the Japanese part is the only single-quoted string in (tpl), and it matches only an input whose root node is 'ky-ouyoLIsHru. ~ By using this distinction of lexical-forrns, we e~n integrate exceptionality handling into the similarity calculation framework without separating this task as a pre process or post-process. ' For iriost peol)le , an exceptional translation pattern is likely to recall a pattern of translation for an i/liomatic or colloquial expression, hi generM, ;in idiomatic translation pattern is a translation pattern whose target part is markedly different from that of translation patterns whose s\u00a2)urce parts am similar to that of the idiomatic pattern. Froni the viewpoint of the transfer process, what we would like to identi[y are translation patterns that may have side-effects when they are selected instead of general translation patterns. We call such translation patterns exceptional travsIation pattern.s. According to this defi nltlon, exceptional translation patterns are not restricted to idiomatic patterns, in fact, more translatlon l)atterns other than idiomatic ones fall into this category. Here: we classify exceptional translation patterns into the following two categories: t Extra-Exceptional Translation l'atterns: These have some. extra elements hi the. target part in addition to those in similar traimhttimi patterns. where .~i is ~L so)lr('e l)art, ti in a target part, an(I mi i~ a mapping from .~'i to iT, then these two translation patterns ;ere called equivalent if they satisfy the following conditions: Step 1 Divide translation patterns into sew~ral groups, each of which consists of equlwdent translation patterns.", | |
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| "text": "Figure 2", | |
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| "text": "Step 2 For each pair of distinct translation pattern groups gl and g~, if any pattern of 9t is equivalent to any pattern of g2 other than nodes governed by the root of the source l)art, tlmn the translation patterns in gl arid 92 are marked gener'~L", | |
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| "text": "Step 3 ~br each pair of distinct translation pattern groups gx and g2, if\" the source part of any pattern (pl) of gl is equivalent to the source part of any pattern of g2, but target parts of them are not struetnrally identical, because Pl ha.s extra elements~ then the translation patterns of gl are marked extm-exeeptionaL", | |
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| "text": "Step 4 For each non-exceptional translation pattern group gl, if there is another general translation pattern group g~ such that any pattern (Pl) of gl is equivMent to any pattern of g2 other than the root node in the target part of Pt, then the translation patterns of gt are marked itth'aexceptional.", | |
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| "text": "Step 2 identifies possible general translation patterns if they are used in a relatively wide range of'words, because in general an exceptional pattern is restricted in the usage of words. This approach, however, is not perfect rot identif,ying general translation patterns, becanse there in ~t c~use such that the exccptionality derives from a single special word. Therefore, in the next step, checking does riot exclude these possible general translation patterns.", | |
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| "text": "Step 3 identities extra-exceptional translation patterns by checking the structure of the target part.", | |
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| "text": "Step 4 then identifies intra-exceptional ones by comparing the mot node in the target part with the root nodes in the target part of possible general translation patterns. The reason why this comparison is restricted to possible general translation patterns is that intra-excepti(n,d translation patterns have si(h~efrects only when they are similar to general translation patterns. Figure 3 shows an example of the identiflcation of exceptional translation patterns, in which the Japanese verbs \"kyouyousuru\" and \"tsukau\" haw.' the same bghcode, and the Japanese nouns \"kuruma,\" \"denwa~\" and \"mahou\" have different bghcodes, on the other hand, \"kuruma\" and \"jitensyd' have the same bg|,eode. First, step 1 divides tImse translation patterns into four groups: group 1 c.onsists of (tpl), group 2 consists of (tp2) and (tp3), group 3 consists of (tp4), and group 4 consists of (tp5).", | |
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| "start": 383, | |
| "end": 391, | |
| "text": "Figure 3", | |
| "ref_id": "FIGREF2" | |
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| "text": "Step 2 identifies group 2 and 3 as general translation patterns, because \"kuruma\" and \"denwa\" have different bghcodes. Subsequently, step 3 identifies (tpl) as an extra-exceptional translation pattern, beci~use (tpl) has extra elements \"the use of\" for (tp~). Further, step 4 identifies (tpS) as at, iutra-exceptional translation pattern, because (tp5) is equivalent to the general translation patterns (tp2), (tp3) and (tp4), other than \"use\" and \"practice\" in the root nodes of the target parts.", | |
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| "text": "We have tested the almve-nientioned algorithm with translation patterns in a Japanese-to-English transfer dictionary that was previously used in our laboratory. For each bghcode, we. collected translation patterns such that the root of the source part has the. code. and a.pplied the algorithm to tim translation pattern set of each category. Table 1 shows the resulting top 10 categories with respect to tt,e total number of occurrences. In most categorles, more than 90% of translation patterns were identified as exceptional. The reason for the lopsidedness of, this result is that tl,e translation patterns described in the pr(~ vious transfer dictionary were almost all exceptional eases that conhl not be. de.all with by the default procedures coded in the transfer module. Therefore, this result indicates that the ~dgorithm is able to idenitfy exceptional translation patterns correctly.", | |
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| "start": 343, | |
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| "text": "Table 1", | |
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| "section": "Experiments", | |
| "sec_num": "4" | |
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| "text": "In conventhmal tra, nsfl,~r systems [4] , transfer rules are roughly divhled into general ones and exceptional (or idiomatic) ones. The transfer system checks the excepth)nal ca.ses first, and if they cannot match the input then the system applies general rules. On the other hand, example-based transfer systems deal with translation patterns (or examples) uniformly on the basis of similarity, according to the example-b~sed pri,ciph,. 'rids m~ci,mism causes the exanlple interference problem. A very useful property of the e\u00d7ample-I)~u~e(l approach is that it allows a sente.nce to be added as an examph~ if it cannot be dealt with properly. This holds if the same input :~s the newly added example is given~ but when the resolution of the slmilarity calculation is not enough, an input that is similar to but not exactly the same as the added example may not be dealt with properly, because there may be another similar example that is exceptional. 'l'hereh)re, it is very important to identify whether an example is general or exceptional.", | |
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| "section": "Discussion", | |
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| "text": "After application of the alg<>rithm described in this paper, translation patterns are classified into the fol-. lowing categories: general, exceptional (extra-and intra-), and neutral. Tabh.' 1: Experime,ltal results for transfer dictionary translation patterns that do not h~ve sld~>effects. They are n(~t used for a wide variety of words in the current translation p~tttern bmse. If m~)re translation patterns are added later, they m~ty be identified as general or exceptional. By this method, mm can enable the system to identify exceptional translation patterns automatically hy adding some general translation I>atterns similar to them. This is a very useful feature for bootstrapping of ~t transh~ti<m pattern base. A weak point of this algorithm, }mwever, is that it requires a large number of translation patterns. If enough translatiml patterns ;~re not given, exceptional translation l)atterns might n(,t be identi tie([, tlowever, collecting many tr;ulslatinn patterns is no longer a serious l)roblern, since several methods for eolleeti,ig them automatically have been pr/q)(Ised in recent studies [2, 11, 14, 6 ].", | |
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| "text": "The method proposed in this paper probad)ly does not comply with human intuition regarding idiomatic translation patterns; rather, it detects transh~timt patterns that are idiomatic for the system, in other words, patterns that might have side-effects in the current set of translati(m patte.rns. It prnl,ahly requires deeper scm~mtle pr()cessing to ide.nti fy transhttion patterns tlu~t are idiomt~tie in the conventional Sellse.", | |
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| "section": "Discussion", | |
| "sec_num": "5" | |
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| { | |
| "text": "In this paper, we have showll a problem of examplebased transfer systems, example inlerfl'lv*u:e, and described a mechanism for dealing with exceptional translation patterns and general translatitm p;ttterns uniformly in similarity calculation withmlt destroyins the whole framework of example-bmsed processing. Further, we have proposed a method fi)r disl.inguishing exceptional translation patterns from general translation patterns. In some cases, this met.h<nt giw~s results that do not match human intuition re-garding idiomatic translation patterns, but it can detect, from the viewpoint of example-based processing, tra.nslatiml p~ttterns in the current translation pattern base that might have side-effects.", | |
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| "section": "Conclusion", | |
| "sec_num": "6" | |
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| ], | |
| "back_matter": [], | |
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| "BIBREF0": { | |
| "ref_id": "b0", | |
| "title": "Cooperation between Transfer and Analysis in l\"~xampleqb~sed Framewc~rk", | |
| "authors": [ | |
| { | |
| "first": "O", | |
| "middle": [], | |
| "last": "Furuse", | |
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| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Iida", | |
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| "year": 1992, | |
| "venue": "Proc. of Coling 92", | |
| "volume": "2", | |
| "issue": "", | |
| "pages": "648--681", | |
| "other_ids": {}, | |
| "num": null, | |
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| "raw_text": "Furuse, O. and Iida, 1l., \"Cooperation between Trans- fer and Analysis in l\"~xampleqb~sed Framewc~rk,\" Proc. of Coling 92, Vol. 2, pp. 648-681, 1992.", | |
| "links": null | |
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| "BIBREF1": { | |
| "ref_id": "b1", | |
| "title": "Learning q'r~mshttion 't'omphttes from Bilingual Text", | |
| "authors": [ | |
| { | |
| "first": "[", | |
| "middle": [], | |
| "last": "Kaji", | |
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| { | |
| "first": "Y", | |
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| "last": "Kid%", | |
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| { | |
| "first": "Y", | |
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| "last": "Morimoto", | |
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| "FIGREF0": { | |
| "text": "el) watashi(1) ha konpyuuta~(computer) wo kyouy-ollsllrll.", | |
| "num": null, | |
| "type_str": "figure", | |
| "uris": null | |
| }, | |
| "FIGREF1": { | |
| "text": "An example-base space scribes a method for identifying exceptional translation patterns. Some experiments are reported in Section 4, and some issues are discussed in Section 5. Finally, some concluding remarks bring this paper to an ond, l';xeeptionM translation l)attern and general i, rans[;tLion pattern SimTlNn calculates the similarity between a subgraph of an input structure and the source part of a translation pattern on the basis of both the structural similarity and the similarity of the lexical-forms of corresponding nodes. For instance, the distance (the inverse of similarity) between two Japanese lexicalforms is expressed by the difference of their values in a Japanese thesaurus called Bunrui-Goi-lIyou [5] 3 as follows: I@hcode(w,) -bgheode(~,,~)[ + distance(wl, w2) = bghmax + b\"", | |
| "num": null, | |
| "type_str": "figure", | |
| "uris": null | |
| }, | |
| "FIGREF2": { | |
| "text": "F, xamI)lc ,)f the identilicati(nl", | |
| "num": null, | |
| "type_str": "figure", | |
| "uris": null | |
| }, | |
| "FIGREF3": { | |
| "text": "Intra-Exceptional \"]'rans[atlon ]>atterns: These are almost same ms similar translation patterns, but several target words are different. of 0\u00d7eeptimial triulslatlon patterns When exceptional translation patterns are [olind~ it is hnportant to know whether two translatiml patterns are e(lUivMent or not. ']'herefore> equivalent translation plctterns are defined as follows: (liven two dependency structures dl and d2, then they lore called equivalent if and only if tiiey are strllerurally identicM and correspmiding nodes have the similar seinantic code. 4 }\"urther~ given two trailslath,n patterns tp, = (si,ti,m,) tp2 = (s2,t2,m2),", | |
| "num": null, | |
| "type_str": "figure", | |
| "uris": null | |
| }, | |
| "FIGREF4": { | |
| "text": "Both sou roe parts axe equivalent> and both targ~t parts are strilctllrally identical. (~) 'l'he roots of l 1 a.nd 17 are the sallle strhlg. For each ,m(le n hi .+~, ',n~(n)is o,,e of transhttion words of n. (4) t,'o~ each ,~o,le ,, in ,\"2, ',,.,('n) is one or translation words of n.", | |
| "num": null, | |
| "type_str": "figure", | |
| "uris": null | |
| } | |
| } | |
| } | |
| } |