Predicate-­‐Argument	
  Structure-­‐based	  Preordering	
  for	  Japanese-­‐English	
  Transla;on	  of	  Scien;ﬁc	  Papers	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  Kenichi	  Ohwada,	  Ryosuke	  Miyazaki	  and	  Mamoru	  Komachi	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  	  Graduate	  School	  of	  System	  Design,	  Tokyo	  Metropolitan	  University	Preordering Method between Japanese and English	Example of Preordering	Japanese : 1. Head-final 2. SOV 3. Postpositionobject	ダイナミックミキシング法 | （ＤＭ法）による | ＴｉＮ膜生成技術を | 			English : 1. Head-initial 2. SVO 3. Preposition	↓Preordering	Improvement of long distance word alignment and performance of machine translationPrevious work	

Extension of rules that we propose			○Hoshino et al., (2013) 	・Rules of sentence-level	Rule 1. Transform a dependency tree from Head-final to Headinitial 	Ext.1. Parenthesis restoration	As a result of Rule 1, parenthesis expressions isreversed, so we modify the rule to restore them.	

the dynamic mixing method (DM)by TiN film generation teqnique		開発した。
predicate	was developed.
	The order of “ダイナミックミキシング法” and	Rule. 1“（ＤＭ法）による” is modidied by Ext. 1.		

開発した。 | ＴｉＮ膜生成技術を | ダイナミックミキシング法 | （ＤＭ	法）による	緩和ケア緩和ケア緩和ケア		 チーム	 （ＰＣＴ）が	
 （ＰＣＴ）が	
 チーム	 チーム	 （ＰＣＴ）が		文書マニュ使用してい移動介助	 現在、	 筋ジストロRule 1Ext. 1	Rule. 2Since there is not a subject, the predicate	アルを	フィー患者の	る (V)	において	
		“開発した” is moved to the end by Ext. 2.	
Ext. 2. Passive voice preordering		Rule 1 	When there’s no subject in a Japanese sentence,(Rule. 3) is skipped because there are no coordinate		
使用してい移動介助筋ジストロ文書マニュwemoveapredicatetotheendof
thesentence現在、	る (V)	において	フィー患者の	アルを	expressions and a full stop in an inappropriate position.	
	
becauseacorrespondingEnglishsentencein
the		
dataofthistaskispassivevoiceinmanycases.	
Rule 2. Transfer of a predicate of a sentence to make SVO	ＴｉＮ膜生成技術を | ダイナミックミキシング法 | （ＤＭ法）による |	If there’s a subject in sentence → just after it	開発した。	
Ext.
3.
Subjectivephrasepreservation	Else if there’s an object → just before it		
AredicateissometimesinsertedinbetweentheElse → just before the predicate’s rightmost dependent	Rule. 4 andFunction word “による” is moved over phrase,	subject and its modifiers by Rule 2, so we change(We used a predicate-argument structure analyzer and judged case of	minor adjustmentbecause the phrase is parenthesis expression.	
the rule to the one that the predicate comes afterが (ga) as subject and case of を (wo), に (ni) as object.)			the subjective phrase (In this case, phrase doesn’tをＴｉＮ膜生成技術 | によるダイナミックミキシング法 | （ＤＭ法） | 	Rule 3. Correct coordinate expressions and punctuations 	mean Bunsetsu).				
た開発し。	
Rule 1Rule3	依存する。
エネルギーコンデン種類と	解説した。	
特徴を	種類と	解説した	特徴を。	
アンプの	
トランスと	 Rule 2 		(V)	は (S)	サに			TiNfilmgenerationtechniquebythedynamicmixing(DM)method
	・Rule of phrase (Bunsetu)-level	Ext. 3 	エネルコンデンRule 4. Reverse content words and function words of each phrase.
トランスと	アンプの	 依存する。	
ギーは	
サに	was developed.	
										Discussion	BLEU	Experimental setting and results Method	  	 RIBES	・Our Proposed Method outperforms our re-implementation of (Hoshino et al., 2013) and・Training data：1 million sentences	
Phrase-­‐based	  SMT	  Baseline	15.74	 0.620162	 the baseline, but the impact on the translation quality is not so large. We think it is・Baseline : SRILM 1.7.0, GIZA++ 1.0.7,	becauseofthepropertyofthisdata,sowewanttotryindifferentdomains.	
(Hoshino	  et	  al.,	  2013)	15.45	0.645954	Moses 2.1.1			・In terms of RIBES, methods including (Hoshino et al., 2013) outperform the baseline, so・PAS Analyzer : Syncha 0.3	Proposed	  Method	  –	  Ext.	  1	 15.73	 0.652461	 we think the effectiveness of preordering is better reflected by RIBES.	
(Mecab 0.996 IPADic 2.7.0)	・When we subtract three modifications one by one from proposed method, the parenthesisProposed	  Method	  –	  Ext.	  2	 15.93	 0.654454	 rule has the largest impact. On Japanese side, 16.8% of sentences have parenthesis
・Distortion limit : 6 (default setting)		
expressions
andabout
0.74%ofparenthesisexpressionscrossoverphrasesinthe
trainingProposed	  Method	  –	  Ext.	  3	 15.88	 0.650964		
data we use.		
Proposed	  Method	16.02	 0.654600	 ・The Passive voice modification doesn’t have much impact, we think it is because the rate	of no-subject sentence is 57% but one of passive voice in English side is not so high.