A Specialised Verb Lexicon as the Basis of Fact Extraction in the Biomedical Domain

Christopher Rupp; Paul Thompson; William Black; John McNaught; Sophia Ananiadou

A Specialised Verb Lexicon as the Basis of Fact Extraction in the Biomedical Domain

Christopher Rupp, Paul Thompson, William Black, John McNaught, Sophia Ananiadou

Research output: Chapter in Book/Conference proceeding › Conference contribution

Abstract

The BioLexicon is a standardised, reusable, lexical and conceptual resource suitable for advanced biomedical text mining. One of the unique features of the BioLexicon is the incorporation of rich syntactic and semantic patterns for a wide range of domain-relevant verbs, which have been acquired semiautomaticallyfrom biomedical corpora. Such types of information can be highly beneficialfor information and fact extraction applications. In this paper, we describe the collection of the verb-specific information for inclusion in the BioLexicon, and explain how it is being employed in a specific scenario (the UKPMC project) to leverage fact-based information extraction on a large collection ofbiomedical papers.

Original language	English
Title of host publication	Proceedings of interdisciplinary workshop on verbs: the identification and representation of verb features (Verb 2010)
Place of Publication	Pisa
Pages	6pp
Publication status	Published - 2010
Event	Interdisciplinary Workshop on Verbs: The identification and representation of verb features (Verb 2010) - Duration: 1 Jan 1824 → …

Conference

Conference	Interdisciplinary Workshop on Verbs: The identification and representation of verb features (Verb 2010)
Period	1/01/24 → …

Access to Document

http://linguistica.sns.it/Workshop_verb/papers/Rupp_verb2010_submission_49.pdf

Cite this

@inproceedings{755c5d118793440898863b204a358a85,

title = "A Specialised Verb Lexicon as the Basis of Fact Extraction in the Biomedical Domain",

abstract = "The BioLexicon is a standardised, reusable, lexical and conceptual resource suitable for advanced biomedical text mining. One of the unique features of the BioLexicon is the incorporation of rich syntactic and semantic patterns for a wide range of domain-relevant verbs, which have been acquired semiautomaticallyfrom biomedical corpora. Such types of information can be highly beneficialfor information and fact extraction applications. In this paper, we describe the collection of the verb-specific information for inclusion in the BioLexicon, and explain how it is being employed in a specific scenario (the UKPMC project) to leverage fact-based information extraction on a large collection ofbiomedical papers.",

author = "Christopher Rupp and Paul Thompson and William Black and John McNaught and Sophia Ananiadou",

note = "1. EC IST FP6-028099 (BOOTStrep)2. UKPMC Funders Group: Arthritis Research Campaign, BBSRC, British Heart Foundation, Cancer Research UK, Chief Scientist Office, Department of Health - National Institute of Health Research, Medical Research Council, Welcome Trust.; Interdisciplinary Workshop on Verbs: The identification and representation of verb features (Verb 2010) ; Conference date: 01-01-1824",

year = "2010",

language = "English",

pages = "6pp",

booktitle = "Proceedings of interdisciplinary workshop on verbs: the identification and representation of verb features (Verb 2010)",

}

Rupp, C, Thompson, P, Black, W, McNaught, J & Ananiadou, S 2010, A Specialised Verb Lexicon as the Basis of Fact Extraction in the Biomedical Domain. in Proceedings of interdisciplinary workshop on verbs: the identification and representation of verb features (Verb 2010). Pisa, pp. 6pp, Interdisciplinary Workshop on Verbs: The identification and representation of verb features (Verb 2010), 1/01/24. <http://linguistica.sns.it/Workshop_verb/papers/Rupp_verb2010_submission_49.pdf>

TY - GEN

T1 - A Specialised Verb Lexicon as the Basis of Fact Extraction in the Biomedical Domain

AU - Rupp, Christopher

AU - Thompson, Paul

AU - Black, William

AU - McNaught, John

AU - Ananiadou, Sophia

N1 - 1. EC IST FP6-028099 (BOOTStrep)2. UKPMC Funders Group: Arthritis Research Campaign, BBSRC, British Heart Foundation, Cancer Research UK, Chief Scientist Office, Department of Health - National Institute of Health Research, Medical Research Council, Welcome Trust.

PY - 2010

Y1 - 2010

N2 - The BioLexicon is a standardised, reusable, lexical and conceptual resource suitable for advanced biomedical text mining. One of the unique features of the BioLexicon is the incorporation of rich syntactic and semantic patterns for a wide range of domain-relevant verbs, which have been acquired semiautomaticallyfrom biomedical corpora. Such types of information can be highly beneficialfor information and fact extraction applications. In this paper, we describe the collection of the verb-specific information for inclusion in the BioLexicon, and explain how it is being employed in a specific scenario (the UKPMC project) to leverage fact-based information extraction on a large collection ofbiomedical papers.

AB - The BioLexicon is a standardised, reusable, lexical and conceptual resource suitable for advanced biomedical text mining. One of the unique features of the BioLexicon is the incorporation of rich syntactic and semantic patterns for a wide range of domain-relevant verbs, which have been acquired semiautomaticallyfrom biomedical corpora. Such types of information can be highly beneficialfor information and fact extraction applications. In this paper, we describe the collection of the verb-specific information for inclusion in the BioLexicon, and explain how it is being employed in a specific scenario (the UKPMC project) to leverage fact-based information extraction on a large collection ofbiomedical papers.

M3 - Conference contribution

SP - 6pp

BT - Proceedings of interdisciplinary workshop on verbs: the identification and representation of verb features (Verb 2010)

CY - Pisa

T2 - Interdisciplinary Workshop on Verbs: The identification and representation of verb features (Verb 2010)

Y2 - 1 January 1824

ER -

A Specialised Verb Lexicon as the Basis of Fact Extraction in the Biomedical Domain

Abstract

Conference

Access to Document

Fingerprint

Cite this