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    <abstract>In this paper, we present ReferenceNet: a semantic-pragmatic network of reference relations between synsets. Synonyms are assumed to be exchangeable in similar contexts and also word embeddings are based on sharing of local contexts represented as vectors. Co-referring words, however, tend to occur in the same topical context but in different local contexts. In addition, they may express different concepts related through topical coherence, and through author framing and perspective. In this paper, we describe how reference relations can be added to WordNet and how they can be acquired. We evaluate two methods of extracting event coreference relations using WordNet relations against a manual annotation of 38 documents within the same topical domain of gun violence. We conclude that precision is reasonable but recall is lower because the WordNet hierarchy does not sufficiently capture the required coherence and perspective relations.</abstract>
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%0 Conference Proceedings
%T ReferenceNet: a semantic-pragmatic network for capturing reference relations.
%A Vossen, Piek
%A Ilievski, Filip
%A Postrma, Marten
%Y Bond, Francis
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 9th Global Wordnet Conference
%D 2018
%8 January
%I Global Wordnet Association
%C Nanyang Technological University (NTU), Singapore
%F vossen-etal-2018-referencenet
%X In this paper, we present ReferenceNet: a semantic-pragmatic network of reference relations between synsets. Synonyms are assumed to be exchangeable in similar contexts and also word embeddings are based on sharing of local contexts represented as vectors. Co-referring words, however, tend to occur in the same topical context but in different local contexts. In addition, they may express different concepts related through topical coherence, and through author framing and perspective. In this paper, we describe how reference relations can be added to WordNet and how they can be acquired. We evaluate two methods of extracting event coreference relations using WordNet relations against a manual annotation of 38 documents within the same topical domain of gun violence. We conclude that precision is reasonable but recall is lower because the WordNet hierarchy does not sufficiently capture the required coherence and perspective relations.
%U https://aclanthology.org/2018.gwc-1.25
%P 219-228

Markdown (Informal)

[ReferenceNet: a semantic-pragmatic network for capturing reference relations.](https://aclanthology.org/2018.gwc-1.25) (Vossen et al., GWC 2018)

• ReferenceNet: a semantic-pragmatic network for capturing reference relations. (Vossen et al., GWC 2018)

ACL

• Piek Vossen, Filip Ilievski, and Marten Postrma. 2018. ReferenceNet: a semantic-pragmatic network for capturing reference relations.. In Proceedings of the 9th Global Wordnet Conference, pages 219–228, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.