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    <titleInfo>
        <title>Semantically Inspired AMR Alignment for the Portuguese Language</title>
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        <namePart type="given">Rafael</namePart>
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        <name type="personal">
            <namePart type="given">Bonnie</namePart>
            <namePart type="family">Webber</namePart>
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        <name type="personal">
            <namePart type="given">Trevor</namePart>
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        <name type="personal">
            <namePart type="given">Yulan</namePart>
            <namePart type="family">He</namePart>
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        <name type="personal">
            <namePart type="given">Yang</namePart>
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    <abstract>Abstract Meaning Representation (AMR) is a graph-based semantic formalism where the nodes are concepts and edges are relations among them. Most of AMR parsing methods require alignment between the nodes of the graph and the words of the sentence. However, this alignment is not provided by manual annotations and available automatic aligners focus only on the English language, not performing well for other languages. Aiming to fulfill this gap, we developed an alignment method for the Portuguese language based on a more semantically matched word-concept pair. We performed both intrinsic and extrinsic evaluations and showed that our alignment approach outperforms the alignment strategies developed for English, improving AMR parsers, and achieving competitive results with a parser designed for the Portuguese language.</abstract>
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        <date>2020-11</date>
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            <start>1595</start>
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%0 Conference Proceedings
%T Semantically Inspired AMR Alignment for the Portuguese Language
%A Anchiêta, Rafael
%A Pardo, Thiago
%Y Webber, Bonnie
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F anchieta-pardo-2020-semantically
%X Abstract Meaning Representation (AMR) is a graph-based semantic formalism where the nodes are concepts and edges are relations among them. Most of AMR parsing methods require alignment between the nodes of the graph and the words of the sentence. However, this alignment is not provided by manual annotations and available automatic aligners focus only on the English language, not performing well for other languages. Aiming to fulfill this gap, we developed an alignment method for the Portuguese language based on a more semantically matched word-concept pair. We performed both intrinsic and extrinsic evaluations and showed that our alignment approach outperforms the alignment strategies developed for English, improving AMR parsers, and achieving competitive results with a parser designed for the Portuguese language.
%R 10.18653/v1/2020.emnlp-main.123
%U https://aclanthology.org/2020.emnlp-main.123
%U https://doi.org/10.18653/v1/2020.emnlp-main.123
%P 1595-1600

Markdown (Informal)

[Semantically Inspired AMR Alignment for the Portuguese Language](https://aclanthology.org/2020.emnlp-main.123) (Anchiêta & Pardo, EMNLP 2020)

• Semantically Inspired AMR Alignment for the Portuguese Language (Anchiêta & Pardo, EMNLP 2020)

ACL

• Rafael Anchiêta and Thiago Pardo. 2020. Semantically Inspired AMR Alignment for the Portuguese Language. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1595–1600, Online. Association for Computational Linguistics.