Treatment of Legal Sentences Including Itemization Written in Japanese, English and Vietnamese —Towards Translation into Logical Forms—
スポンサーリンク
概要
- 論文の詳細を見る
This paper reports how to treat legal sentences including itemized expressions in three languages. Thus far, we have developed a system for translating legal sentences into logical formulae. Although our system basically converts words and phrases in a target sentence into predicates in a logical formula, it generates some useless predicates for itemized and referential expressions. In the previous study, focusing on Japanese Law, we have made a front end system which substitutes corresponding referent phrases for these expressions. In this paper, we examine our approach to the Vietnamese Law and the United States Code. Our linguistic analysis shows the difference in notation among languages or nations, and we extracted conventional expressions denoting itemization for each language. The experimental result shows high accuracy in terms of generating independent, plain sentences from the law articles including itemization. The proposed system generates a meaningful text with high readability, which can be input into our translation system.
- Information and Media Technologies 編集運営会議の論文
著者
-
Shimazu Akira
School Of Information Science Japan Advanced Institute Of Science And Technology
-
Nguyen Le
School Of Information Science Japan Advanced Institute Of Science And Technology
-
Pham Minh
School Of Information Science Japan Advanced Institute Of Science And Technology
-
KIMURA Yusuke
School of Information Science, Japan Advanced Institute of Science and Technology
-
Kimura Yusuke
School Of Information Science Japan Advanced Institute Of Science And Technology
-
Nakamura Makoto
School Of Information Science Japan Advanced Institute Of Science And Technology
-
PHAM Minh
School of Information Science, Japan Advanced Institute of Science and Technology
関連論文
- Word Sense Disambiguation by Combining Classifiers with an Adaptive Selection of Context Representation
- Word Sense Disambiguation by Combining Classifiers with an Adaptive Selection of Context Representation
- Using Semi-supervised Learning for Question Classification
- Automatic Extraction of the Fine Category of Person Named Entities from Text Corpora
- A Semi Supervised Learning Model for Mapping sentences to logical form with ambiguous supervision
- Treatment of Legal Sentences Including Itemization Written in Japanese, English and Vietnamese —Towards Translation into Logical Forms—
- Clause Splitting with Conditional Random Fields
- Learning to Generate a Table-of-Contents with Supportive Knowledge
- Clause Splitting with Conditional Random Fields
- Using shallow semantic parsing and relation extraction for finding contradiction in text
- Treatment of Legal Sentences Including Itemization Written in Japanese, English and Vietnamese —Towards Translation into Logical Forms—
- Using Semi-supervised Learning for Question Classification