tailieunhanh - Báo cáo khoa học: "Rich bitext projection features for parse reranking"

Many different types of features have been shown to improve accuracy in parse reranking. A class of features that thus far has not been considered is based on a projection of the syntactic structure of a translation of the text to be parsed. The intuition for using this type of bitext projection feature is that ambiguous structures in one language often correspond to unambiguous structures in another. We show that reranking based on bitext projection features increases parsing accuracy significantly. . | Rich bitext projection features for parse reranking Alexander Fraser Renjing Wang Hinrich Schutze Institute for Natural Language Processing University of Stuttgart fraser wangrg @ Abstract Many different types of features have been shown to improve accuracy in parse reranking. A class of features that thus far has not been considered is based on a projection of the syntactic structure of a translation of the text to be parsed. The intuition for using this type of bitext projection feature is that ambiguous structures in one language often correspond to unambiguous structures in another. We show that reranking based on bitext projection features increases parsing accuracy significantly. 1 Introduction Parallel text or bitext is an important knowledge source for solving many problems such as machine translation cross-language information retrieval and the projection of linguistic resources from one language to another. In this paper we show that bitext-based features are effective in addressing another NLP problem increasing the accuracy of statistical parsing. We pursue this approach for a number of reasons. First one limiting factor for syntactic approaches to statistical machine translation is parse quality Quirk and Corston-Oliver 2006 . Improved parses of bitext should result in improved machine translation. Second as more and more texts are available in several languages it will be increasingly the case that a text to be parsed is itself part of a bitext. Third we hope that the improved parses of bitext will serve as higher quality training data for improving monolingual parsing using a process similar to self-training McClosky et al. 2006 . It is well known that different languages encode different types of grammatical information agreement case tense etc. and that what can be left unspecified in one language must be made explicit NP Figure 1 English parse with high attachment who had gray hair in another. This information can be used for .

• Báo cáo khoa học
• Rich bitext projection features
• parse reranking
• Alexander Fraser
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• Long Papers
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln