2012 IdentifyingUntypedRelationMenti

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Subject Headings: Relation Mention Identification, SDOI System.

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Abstract

In this paper we present the SDOIrmi text graph-based semi-supervised algorithm for the task for relation mention identification when the underlying concept mentions have already been identified and linked to an ontology. To overcome the lack of annotated data, we propose a labelling heuristic based on information extracted from the ontology. We evaluated the algorithm on the kdd09cma1 dataset using a leave-one-document-out framework and demonstrated an increase in F1 in performance over a co-occurrence based AllTrue baseline algorithm. An extrinsic evaluation of the predictions suggests a worthwhile precision on the more confidently predicted additions to the ontology.

References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2012 IdentifyingUntypedRelationMentiGabor MelliIdentifying Untyped Relation Mentions in a Corpus Given An Ontology2012
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