TAILIEUCHUNG - Báo cáo khoa học: "Aspectual Type and Temporal Relation Classification"

In this paper we investigate the relevance of aspectual type for the problem of temporal information processing, . the problems of the recent TempEval challenges. For a large list of verbs, we obtain several indicators about their lexical aspect by querying the web for expressions where these verbs occur in contexts associated with specific aspectual types. We then proceed to extend existing solutions for the problem of temporal information processing with the information extracted this way. . | Aspectual Type and Temporal Relation Classification Francisco Costa Universidade de Lisboa fcosta@ Antonio Branco Universidade de Lisboa Abstract In this paper we investigate the relevance of aspectual type for the problem of temporal information processing . the problems of the recent TempEval challenges. For a large list of verbs we obtain several indicators about their lexical aspect by querying the web for expressions where these verbs occur in contexts associated with specific aspectual types. We then proceed to extend existing solutions for the problem of temporal information processing with the information extracted this way. The improved performance of the resulting models shows that i aspectual type can be data-mined with unsupervised methods with a level of noise that does not prevent this information from being useful and that ii temporal information processing can profit from information about aspectual type. 1 Introduction Extracting the temporal information present in a text is relevant to many natural language processing applications including question-answering information extraction and even document summarization as summaries may be more readable if they follow a chronological order. Recent evaluation campaigns have focused on the extraction of temporal information from written text. TempEval Verhagen et al. 2007 in 2007 and more recently TempEval-2 Verhagen et al. 2010 in 2010 were concerned with this problem. Additionally they provided data that can be used to develop and evaluate systems that can automatically temporally tag natural language text. These data are annotated according to the TimeML Pustejovsky et al. 2003 scheme. Figure 1 shows a small and slightly simplified fragment of the data from TempEval with TimeML annotations. There event terms such as the term referring to the event of releasing the tapes are annotated using EVENT tags. States such as the situations denoted by verbs like want or .

• Báo cáo khoa học
• Aspectual Type
• Temporal Relation Classification
• Francisco Costa
• 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