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        <title>FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System</title>
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            <namePart type="family">Apidianaki</namePart>
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            <namePart type="given">Saif</namePart>
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            <namePart type="given">Jonathan</namePart>
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    <abstract>We present the approach developed at the Faculty of Engineering of the University of Porto to participate in SemEval-2018 Task 5: Counting Events and Participants within Highly Ambiguous Data covering a very long tail. The work described here presents the experimental system developed to extract entities from news articles for the sake of Question Answering. We propose a supervised learning approach to enable the recognition of two different types of entities: Locations and Participants. We also discuss the use of distance-based algorithms (using Levenshtein distance and Q-grams) for the detection of documents’ closeness based on the entities extracted. For the experiments, we also used a multi-agent system that improved the performance.</abstract>
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%0 Conference Proceedings
%T FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System
%A Abreu, Carla
%A Oliveira, Eugénio
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Bethard, Steven
%Y Carpuat, Marine
%S Proceedings of the 12th International Workshop on Semantic Evaluation
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F abreu-oliveira-2018-feup
%X We present the approach developed at the Faculty of Engineering of the University of Porto to participate in SemEval-2018 Task 5: Counting Events and Participants within Highly Ambiguous Data covering a very long tail. The work described here presents the experimental system developed to extract entities from news articles for the sake of Question Answering. We propose a supervised learning approach to enable the recognition of two different types of entities: Locations and Participants. We also discuss the use of distance-based algorithms (using Levenshtein distance and Q-grams) for the detection of documents’ closeness based on the entities extracted. For the experiments, we also used a multi-agent system that improved the performance.
%R 10.18653/v1/S18-1109
%U https://aclanthology.org/S18-1109
%U https://doi.org/10.18653/v1/S18-1109
%P 667-673

Markdown (Informal)

[FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System](https://aclanthology.org/S18-1109) (Abreu & Oliveira, SemEval 2018)

• FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System (Abreu & Oliveira, SemEval 2018)

ACL

• Carla Abreu and Eugénio Oliveira. 2018. FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 667–673, New Orleans, Louisiana. Association for Computational Linguistics.