2003 InformationExtraction

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Subject Headings: Information Extraction Task, Named Entity Recognition Task, Event Extraction Task.


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30.1 Name Identification and Classification

30.1.1 Building a name tagger

  • In conventional treatments of language structure, little attention is paid to proper names, addresses, quantity phrases, etc. Presentations of language analysis typically begin by looking words up in a dictionary and identifying them as noun, verbs, adjectives, etc. In fact, however, most tests include lots of names, and if a system cannot identify these as linguistic units (and, for most tasks, identify their type), it will be hard pressed to produce a linguistic analysis of the text.

30.2 Event Extraction

  • We now consider a more complex task: extracting all the instances of a particular type of relationship or event from text. For example, we may have a file of seminar announcements and want to build a table listing the speaker, title, date, time, and location of each seminar.



 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2003 InformationExtractionRalph GrishmanInformation Extraction