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    <titleInfo>
        <title>Possessors Change Over Time: A Case Study with Artworks</title>
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        <namePart type="given">Dhivya</namePart>
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    <abstract>This paper presents a corpus and experimental results to extract possession relations over time. We work with Wikipedia articles about artworks, and extract possession relations along with temporal information indicating when these relations are true. The annotation scheme yields many possessors over time for a given artwork, and experimental results show that an LSTM ensemble can automate the task.</abstract>
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    <identifier type="doi">10.18653/v1/D18-1251</identifier>
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%0 Conference Proceedings
%T Possessors Change Over Time: A Case Study with Artworks
%A Chinnappa, Dhivya
%A Blanco, Eduardo
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F chinnappa-blanco-2018-possessors
%X This paper presents a corpus and experimental results to extract possession relations over time. We work with Wikipedia articles about artworks, and extract possession relations along with temporal information indicating when these relations are true. The annotation scheme yields many possessors over time for a given artwork, and experimental results show that an LSTM ensemble can automate the task.
%R 10.18653/v1/D18-1251
%U https://aclanthology.org/D18-1251
%U https://doi.org/10.18653/v1/D18-1251
%P 2278-2287

Markdown (Informal)

[Possessors Change Over Time: A Case Study with Artworks](https://aclanthology.org/D18-1251) (Chinnappa & Blanco, EMNLP 2018)

• Possessors Change Over Time: A Case Study with Artworks (Chinnappa & Blanco, EMNLP 2018)

ACL

• Dhivya Chinnappa and Eduardo Blanco. 2018. Possessors Change Over Time: A Case Study with Artworks. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2278–2287, Brussels, Belgium. Association for Computational Linguistics.