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Catching the common cause: extraction and annotation of causal relations and their participants

  • In this paper, we present a simple, yet effective method for the automatic identification and extraction of causal relations from text, based on a large English-German parallel corpus. The goal of this effort is to create a lexical resource for German causal relations. The resource will consist of a lexicon that describes constructions that trigger causality as well as the participants of the causal event, and will be augmented by a corpus with annotated instances for each entry, that can be used as training data to develop a system for automatic classification of causal relations. Focusing on verbs, our method harvested a set of 100 different lexical triggers of causality, including support verb constructions. At the moment, our corpus includes over 1,000 annotated instances. The lexicon and the annotated data will be made available to the research community.

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Metadaten
Author:Ines Rehbein, Josef RuppenhoferGND
URN:urn:nbn:de:bsz:mh39-61534
URL:https://sigann.github.io/LAW-XI-2017/papers/LAW13.pdf
ISBN:978-1-945626-39-5
Parent Title (English):Proceedings of the 11th Linguistic Annotation Workshop at EACL 2017 (The LAW XI), Valencia, Spain, 2017
Publisher:EACL
Place of publication:Stroudsburg, PA
Document Type:Conference Proceeding
Language:English
Year of first Publication:2017
Date of Publication (online):2017/05/08
Publicationstate:Veröffentlichungsversion
Reviewstate:Peer-review
GND Keyword:Annotation; Automatische Sprachanalyse; Computerlinguistik; Kausalität; Korpus <Linguistik>
First Page:105
Last Page:114
Dewey Decimal Classification:400 Sprache / 400 Sprache, Linguistik
Leibniz-Classification:Sprache, Linguistik
Linguistics-Classification:Computerlinguistik
Open Access?:Ja
Licence (German):Es gilt das UrhG