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        <title>Language Resources and Annotation Tools for Cross-Sentence Relation Extraction</title>
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    <abstract>In this paper, we present a novel combination of two types of language resources dedicated to the detection of relevant relations (RE) such as events or facts across sentence boundaries. One of the two resources is the sar-graph, which aggregates for each target relation ten thousands of linguistic patterns of semantically associated relations that signal instances of the target relation (Uszkoreit and Xu, 2013). These have been learned from the Web by intra-sentence pattern extraction (Krause et al., 2012) and after semantic filtering and enriching have been automatically combined into a single graph. The other resource is cockrACE, a specially annotated corpus for the training and evaluation of cross-sentence RE. By employing our powerful annotation tool Recon, annotators mark selected entities and relations (including events), coreference relations among these entities and events, and also terms that are semantically related to the relevant relations and events. This paper describes how the two resources are created and how they complement each other.</abstract>
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%0 Conference Proceedings
%T Language Resources and Annotation Tools for Cross-Sentence Relation Extraction
%A Krause, Sebastian
%A Li, Hong
%A Xu, Feiyu
%A Uszkoreit, Hans
%A Hummel, Robert
%A Spielhagen, Luise
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 may
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F krause-etal-2014-language
%X In this paper, we present a novel combination of two types of language resources dedicated to the detection of relevant relations (RE) such as events or facts across sentence boundaries. One of the two resources is the sar-graph, which aggregates for each target relation ten thousands of linguistic patterns of semantically associated relations that signal instances of the target relation (Uszkoreit and Xu, 2013). These have been learned from the Web by intra-sentence pattern extraction (Krause et al., 2012) and after semantic filtering and enriching have been automatically combined into a single graph. The other resource is cockrACE, a specially annotated corpus for the training and evaluation of cross-sentence RE. By employing our powerful annotation tool Recon, annotators mark selected entities and relations (including events), coreference relations among these entities and events, and also terms that are semantically related to the relevant relations and events. This paper describes how the two resources are created and how they complement each other.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/422_Paper.pdf
%P 4320-4325

Markdown (Informal)

[Language Resources and Annotation Tools for Cross-Sentence Relation Extraction](http://www.lrec-conf.org/proceedings/lrec2014/pdf/422_Paper.pdf) (Krause et al., LREC 2014)

• Language Resources and Annotation Tools for Cross-Sentence Relation Extraction (Krause et al., LREC 2014)

ACL

• Sebastian Krause, Hong Li, Feiyu Xu, Hans Uszkoreit, Robert Hummel, and Luise Spielhagen. 2014. Language Resources and Annotation Tools for Cross-Sentence Relation Extraction. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4320–4325, Reykjavik, Iceland. European Language Resources Association (ELRA).