2002 FineGrainedProperNounOnts

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Subject Headings: WordNet Database, ProperNoun, Lexical Ontology, Proper Noun Ontology.

Notes

  • Quote: Unfortunately, building a proper noun ontology is more difficult than building a common noun ontology, since the set of proper nouns grows more rapidly. New people are born.

Quotes

Abstract

1 Introduction

  • The WordNet lexical ontology (Miller, 1990) contains more than 100,000 unique noun forms. Most of these noun forms are common nouns (nouns describing non-specific members of a general class, e.g. “detective”). Only a small percentage1 of the nouns in WordNet are proper nouns (nouns describing specific instances, e.g. “[the detective] Columbo”).
  • The WordNet ontology has been widely useful, with applications in information retrieval (Sussna, 1993), text classification (Scott and Matwin, 1998), and question answering (Pasca and Harabagiu, 2001). These successes have shown that common noun ontologies have wide applicability and utility.
  • There exists no ontology with similar coverage and detail for proper nouns. Prior work in proper noun identification has focused on ’named entity’ recognition (Chinchor et al., 1999), stemming from the MUC evaluations. In this task, each proper noun is categorized, for example, as a PERSON, a LOCATION, or an ORGANIZATION.
  • Unfortunately, building a proper noun ontology is more difficult than building a common noun ontology, since the set of proper nouns grows more rapidly. New people are born.,


 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2002 FineGrainedProperNounOntsGideon S. MannFine-Grained Proper Noun Ontologies for Question AnsweringProceedings of the Worshop on Building and Using Semantic Networkshttp://dx.doi.org/10.3115/1118735.111874610.3115/1118735.11187462002