Desenvolvimento e avaliação de um modelo NER no domínio da análise cultural e do turismo

  1. Sotelo Docío, Susana 1
  2. Gamallo, Pablo 1
  3. Iriarte, Álvaro 2
  1. 1 Universidade de Santiago de Compostela
    info

    Universidade de Santiago de Compostela

    Santiago de Compostela, España

    ROR https://ror.org/030eybx10

  2. 2 Universidade do Minho
    info

    Universidade do Minho

    Braga, Portugal

    ROR https://ror.org/037wpkx04

Revista:
Linguamática

ISSN: 1647-0818

Ano de publicación: 2023

Volume: 15

Número: 2

Páxinas: 3-18

Tipo: Artigo

DOI: 10.21814/LM.15.2.405 DIALNET GOOGLE SCHOLAR lock_openAcceso aberto editor

Outras publicacións en: Linguamática

Obxectivos de Desenvolvemento Sustentable

Resumo

 O Reconhecimento de Entidades Mencionadas (NER) é uma tarefa essencial de extracção de informação em que as entidades de um texto são identificadas e classificadas. Um dos principais desafios enfrentados pelos sistemas NER é a dificuldade de generalização do aprendido para outros tipos de corpora diferentes dos utilizados durante o treino. Este problema é acentuado pelo facto de a maioria dos corpora de treino utilizados serem de natureza jornalística e, portanto, precisarem de ser adaptados a outros géneros e domínios. Neste artigo, utilizamos um corpus espanhol composto por entrevistas a visitantes da cidade de Santiago de Compostela e anotado com entidades mencionadas, para a avaliação e treino de sistemas NER adaptados ao domínio da cultura e do turismo. Apresentamos uma comparação das diferentes abordagens aplicadas, desde algoritmos clássicos de aprendizagem automática ao afinamento de vários modelos de Transformers. Os resultados obtidos superam significativamente o baseline, representado aqui pelos toolkits Stanza, spaCy e Flair, embora os testes preliminares com entidades não observadas durante o treino sugiram a necessidade de avaliações adicionais da sua capacidade de generalização e o uso de um método de segmentação adversarial no corpus.

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