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    <titleInfo>
        <title>Amharic Question Answering for Biography, Definition, and Description Questions</title>
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    <name type="personal">
        <namePart type="given">Tilahun</namePart>
        <namePart type="given">Abedissa</namePart>
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    <name type="personal">
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            <title>Proceedings of the 2019 Workshop on Widening NLP</title>
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            <namePart type="given">Diyi</namePart>
            <namePart type="family">Yang</namePart>
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            <namePart type="given">Rossana</namePart>
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            <namePart type="family">Waseem</namePart>
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    <abstract>A broad range of information needs can often be stated as a question. Question Answering (QA) systems attempt to provide users concise answer(s) to natural language questions. The existing Amharic QA systems handle fact-based questions that usually take named entities as an answer. To deal with more complex information needs we developed an Amharic non-factoid QA for biography, definition, and description questions. A hybrid approach has been used for the question classification. For document filtering and answer extraction we have used lexical patterns. On the other hand to answer biography questions we have used a summarizer and the generated summary is validated using a text classifier. Our QA system is evaluated and has shown a promising result.</abstract>
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            <start>110</start>
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%0 Conference Proceedings
%T Amharic Question Answering for Biography, Definition, and Description Questions
%A Taffa, Tilahun Abedissa
%A Libsie, Mulugeta
%Y Axelrod, Amittai
%Y Yang, Diyi
%Y Cunha, Rossana
%Y Shaikh, Samira
%Y Waseem, Zeerak
%S Proceedings of the 2019 Workshop on Widening NLP
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F taffa-libsie-2019-amharic
%X A broad range of information needs can often be stated as a question. Question Answering (QA) systems attempt to provide users concise answer(s) to natural language questions. The existing Amharic QA systems handle fact-based questions that usually take named entities as an answer. To deal with more complex information needs we developed an Amharic non-factoid QA for biography, definition, and description questions. A hybrid approach has been used for the question classification. For document filtering and answer extraction we have used lexical patterns. On the other hand to answer biography questions we have used a summarizer and the generated summary is validated using a text classifier. Our QA system is evaluated and has shown a promising result.
%U https://aclanthology.org/W19-3635
%P 110-113

Markdown (Informal)

[Amharic Question Answering for Biography, Definition, and Description Questions](https://aclanthology.org/W19-3635) (Taffa & Libsie, WiNLP 2019)

• Amharic Question Answering for Biography, Definition, and Description Questions (Taffa & Libsie, WiNLP 2019)

ACL

• Tilahun Abedissa Taffa and Mulugeta Libsie. 2019. Amharic Question Answering for Biography, Definition, and Description Questions. In Proceedings of the 2019 Workshop on Widening NLP, pages 110–113, Florence, Italy. Association for Computational Linguistics.