Named Entities
Recognition, classification and use
Editors
Named Entities provides critical information for many NLP applications. Named Entity recognition and classification (NERC) in text is recognized as one of the important sub-tasks of Information Extraction (IE). The seven papers in this volume cover various interesting and informative aspects of NERC research. Nadeau & Sekine provide an extensive survey of past NERC technologies, which should be a very useful resource for new researchers in this field. Smith & Osborne describe a machine learning model which tries to solve the over-fitting problem. Mazur & Dale tackle a common problem of NE and conjunction; as conjunctions are often a part of NEs or appear close to NEs, this is an important practical problem. A further three papers describe analyses and implementations of NERC for different languages: Spanish (Galicia-Haro & Gelbukh), Bengali (Ekbal, Naskar & Bandyopadhyay), and Serbian (Vitas, Krstev & Maurel). Finally, Steinberger & Pouliquen report on a real WEB application where multilingual NERC technology is used to identify occurrences of people, locations and organizations in newspapers in different languages.
The contributions to this volume were previously published in Lingvisticae Investigationes 30:1 (2007).
[Benjamins Current Topics, 19] 2009. v, 168 pp.
Publishing status: Available
© John Benjamins Publishing Company
Table of Contents
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Foreword | pp. 1–2
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Articles
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A survey of named entity recognition and classificationDavid Nadeau and Satoshi Sekine | pp. 3–28
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Diversity in logarithmic opinion poolsAndrew D.M. Smith and Miles Osborne | pp. 29–50
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Handling conjunctions in named entitiesPawel Mazur and Robert Dale | pp. 51–70
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Complex named entities in Spanish texts: Structures and propertiesSofía N. Galicia-Haro and Alexander Gelbukh | pp. 71–96
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Named Entity Recognition and transliteration in BengaliAsif Ekbal, Sudip Kumar Naskar and Sivaji Bandyopadhyay | pp. 97–116
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A note on the semantic and morphological properties of proper names in the Prolex projectDuško Vitas, Cvetana Krstev and Denis Maurel | pp. 117–136
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Cross-lingual Named Entity RecognitionRalf Steinberger and Bruno Pouliquen | pp. 137–164
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Index | pp. 165–168
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This list is based on CrossRef data as of 6 march 2023. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.
Subjects & Metadata
BIC Subject: CFG – Semantics, Pragmatics, Discourse Analysis
BISAC Subject: LAN009000 – LANGUAGE ARTS & DISCIPLINES / Linguistics / General