Aligning Texts and Knowledge Bases with Semantic Sentence Simplification
Aligning Texts and Knowledge Bases with Semantic Sentence Simplification
The linked repository contains the resultant datasets of the Semantic Sentence Simplification (S3) methodology. Two high quality data-to-text corpora have been built: (i) DBpedia triples aligned with single Wikipedia sentences and (ii) triples from the Unified Medical Language System (UMLS) aligned with single MedlinePlus sentences.
University of Southampton
Mrabet, Yassine
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Vougiouklis, Pavlos
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Kilicoglu, Halil
3e451da8-9a6b-4b06-a06f-a34552930ccf
Gardent, Claire
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Demner-Fushman, Dina
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Hare, Jonathon
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Simperl, Elena
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Mrabet, Yassine
7f194bd5-ab6f-4371-b03b-8afe8e0b7034
Vougiouklis, Pavlos
4cd0a8f1-c5e2-4ba2-8dcd-753db616b215
Kilicoglu, Halil
3e451da8-9a6b-4b06-a06f-a34552930ccf
Gardent, Claire
40e0be0c-2a9e-4774-9768-06ae7a3ab120
Demner-Fushman, Dina
2d8700ee-dfee-49cb-958d-e0ef412ed4a1
Hare, Jonathon
65ba2cda-eaaf-4767-a325-cd845504e5a9
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
Mrabet, Yassine and Vougiouklis, Pavlos
(2016)
Aligning Texts and Knowledge Bases with Semantic Sentence Simplification.
University of Southampton
[Dataset]
Abstract
The linked repository contains the resultant datasets of the Semantic Sentence Simplification (S3) methodology. Two high quality data-to-text corpora have been built: (i) DBpedia triples aligned with single Wikipedia sentences and (ii) triples from the Unified Medical Language System (UMLS) aligned with single MedlinePlus sentences.
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More information
Published date: May 2016
Organisations:
Electronics & Computer Science, Vision, Learning and Control, Web and Internet Science
Identifiers
Local EPrints ID: 427380
URI: http://eprints.soton.ac.uk/id/eprint/427380
PURE UUID: 0c21b6e1-bd0b-4c46-bbbe-e9cca51ad474
Catalogue record
Date deposited: 14 Jan 2019 17:31
Last modified: 06 May 2023 01:41
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Contributors
Creator:
Yassine Mrabet
Creator:
Pavlos Vougiouklis
Contributor:
Halil Kilicoglu
Research team head:
Claire Gardent
Research team head:
Dina Demner-Fushman
Research team head:
Jonathon Hare
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