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        <title>Reconstructing the house from the ad: Structured prediction on real estate classifieds</title>
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        <namePart type="given">Giannis</namePart>
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        <namePart type="given">Chris</namePart>
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            <namePart type="given">Mirella</namePart>
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            <namePart type="given">Phil</namePart>
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    <abstract>In this paper, we address the (to the best of our knowledge) new problem of extracting a structured description of real estate properties from their natural language descriptions in classifieds. We survey and present several models to (a) identify important entities of a property (e.g.,rooms) from classifieds and (b) structure them into a tree format, with the entities as nodes and edges representing a part-of relation. Experiments show that a graph-based system deriving the tree from an initially fully connected entity graph, outperforms a transition-based system starting from only the entity nodes, since it better reconstructs the tree.</abstract>
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%0 Conference Proceedings
%T Reconstructing the house from the ad: Structured prediction on real estate classifieds
%A Bekoulis, Giannis
%A Deleu, Johannes
%A Demeester, Thomas
%A Develder, Chris
%Y Lapata, Mirella
%Y Blunsom, Phil
%Y Koller, Alexander
%S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F bekoulis-etal-2017-reconstructing
%X In this paper, we address the (to the best of our knowledge) new problem of extracting a structured description of real estate properties from their natural language descriptions in classifieds. We survey and present several models to (a) identify important entities of a property (e.g.,rooms) from classifieds and (b) structure them into a tree format, with the entities as nodes and edges representing a part-of relation. Experiments show that a graph-based system deriving the tree from an initially fully connected entity graph, outperforms a transition-based system starting from only the entity nodes, since it better reconstructs the tree.
%U https://aclanthology.org/E17-2044/
%P 274-279

Markdown (Informal)

[Reconstructing the house from the ad: Structured prediction on real estate classifieds](https://aclanthology.org/E17-2044/) (Bekoulis et al., EACL 2017)

• Reconstructing the house from the ad: Structured prediction on real estate classifieds (Bekoulis et al., EACL 2017)

ACL

• Giannis Bekoulis, Johannes Deleu, Thomas Demeester, and Chris Develder. 2017. Reconstructing the house from the ad: Structured prediction on real estate classifieds. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 274–279, Valencia, Spain. Association for Computational Linguistics.