TAILIEUCHUNG - Báo cáo khoa học: "Detecting Errors in Part-of-Speech Annotation"

We propose a new method for detecting errors in "gold-standard" part-ofspeech annotation. The approach locates errors with high precision based on n-grams occurring in the corpus with multiple taggings. Two further techniques, closed-class analysis and finitestate tagging guide patterns, are discussed. The success of the three approaches is illustrated for the Wall Street Journal corpus as part of the Penn Treebank. | Detecting Errors in Part-of-Speech Annotation Markus Dickinson Department of Linguistics The Ohio State University dickinso@ w. Detmar Meurers Department of Linguistics The Ohio State University dm@ Abstract We propose a new method for detecting errors in gold-standard part-of-speech annotation. The approach locates errors with high precision based on n-grams occuưing in the corpus with multiple taggings. Two further techniques closed-class analysis and finite-state tagging guide patterns are discussed. The success of the three approaches is illustrated for the Wall Street Journal corpus as part of the Penn Treebank. 1 Introduction Part-of-speech pos annotated reference corpora such as the British National Corpus Leech et al. 1994 the Penn Treebank Marcus et al. 1993 or the German Negra Treebank Skut et al. 1997 play an important role for current work in computational linguistics. They provide training material for research on tagging algorithms and they serve as a gold standard for evaluating the performance of such tools. High quality pos-annotated text is also relevant as input for syntactic processing for practical applications such as information extraction and for linguistic research making use of pos-based corpus queries. The gold-standard pos-annotation for such large reference corpora is generally obtained using an automatic tagger to produce a first annotation followed by human post-editing. While Sinclair 1992 provides some arguments for prioritizing a fully automated analysis human post-editing has been shown to significantly reduce the number of pos-annotation errors. Brants 2000 discusses that a single human post-editor reduces the error rate in the STTS annotation of the German Negra corpus produced by the TnT tagger to . Baker 1997 also reports an improvement of around 2 for a similar experiment carried out for an English sample originally tagged with accuracy by the CLAWS tagger. And Leech 1997 reports that .

• Báo cáo khoa học
• Detecting Errors
• Part of Speech Annotation
• Markus Dickinson
• scientific reports
• model language
• process natural language
• Automatically Parsed Dependency Relations
• Markus Dickinson Indiana
• báo cáo khoa học
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• A Feedback Augmented Method
• Detecting Errors in the Writing
• Learners of English
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Discontinuous Structural Annotation
• From detecting errors
• automatically correcting them
• Lecture Wireless networks
• Wireless networks
• Bài giảng Mạng không dây
• Error detecting
• Correcting techniques
• Transmission errors
• Cyclic redundancy check
• Emission and Function
• Volatile Organic
• Compounds in Response
• Abiotic Stress
• Epigenetic Chromatin
• Regulators as Mediators
• Programming languages
• Lecture Programming languages
• Ngôn ngữ lập trình
• Detecting type errors
• Type systems
• Formalizing the clite type system
• 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