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CQL Grammars for Lexical and Semantic Information Extraction for Portuguese and Italian

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Computational Processing of the Portuguese Language (PROPOR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13208))

Abstract

The anchorage to real data is one of the main parameters that guarantees the quality and the coverage of lexical resources, especially in the context of specialized domains. Thus, lexicon extraction from corpora is a consensual method for building lexical resources. However, given that data validation by experts in specialized contexts is a necessary step, the automatic screening of data becomes fundamental to maximize the informational value of the interaction with experts. In this paper we present and discuss a hybrid methodology, combining linguistic and statistical approaches, focusing on the extraction of specialized lexical units and salient semantic information using CQL grammars. The proposed method involves several steps, from frequency information analyses, concordances and collocations extraction to manual revision and expert validation and encompasses the construction and application of knowledge-based patterns CQL grammars. We present two CQL grammars for lexical and semantic information extraction developed for Portuguese and Italian and evaluate results from its application to specialized corpora on Public Art domain, demonstrating the value of this method for lexicon and semantic information extraction from large data.

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Notes

  1. 1.

    CQL was devised by Schulze and Christ [35].

  2. 2.

    According to Meyer, 2001, paralinguistic patterns are not strictly grammatical or lexical and include punctuation and other elements from the general structure of a text.

  3. 3.

    These CQL grammars will be available soon through Sketch Engine Sketch Grammars and CLUNL resources webpage (https://clunl.fcsh.unl.pt/en/online-resources/).

  4. 4.

    Structures that point to instrument_result relations seem very productive within the Public Art domain, but eventually in other domains probably not.

  5. 5.

    N:1 = “artista” [lemma = “usar”] [tag = “S.*” ‘de’]? N:2 =  “forma” [tag = “A.*” ‘deliberada’].

  6. 6.

    “Não entendem a arte como produção de obras unitárias” | They do not understand art as the production of unique works.

  7. 7.

    1NP + be + punctuation + portanto|então + 2NP.

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Acknowledgments

I would like to thank Raquel Amaro for the insights and the discussion of parts of this paper and the anonymous reviewers for all the useful critiques and suggestions.

This research is supported by Portuguese national funding through the FCT – Portuguese Foundation for Science and Technology as part of the project of CLUNL School of Social Sciences and Humanities, NOVA University Lisbon, 1069-061 Lisboa, Portugal (UIDB/LIN/03213/2020 and UIDP/LIN/03213/2020), and by the PhD grant (PD/BD/128131/2016).

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Authors and Affiliations

  1. Linguistic Research Centre of NOVA University Lisbon, Lisbon, Portugal

    Chiara Barbero

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  1. Chiara Barbero
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Correspondence to Chiara Barbero .

Editor information

Editors and Affiliations

  1. Universidade de Fortaleza, Fortaleza, Brazil

    Vládia Pinheiro

  2. CiTIUS - Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Pablo Gamallo

  3. Universidade Nova de Lisboa, Lisbon, Portugal

    Raquel Amaro

  4. University of Sheffield, Sheffield, UK

    Carolina Scarton

  5. INESC-ID, Lisbon, Portugal

    Fernando Batista

  6. Federal University of São Carlos, São Carlos, Brazil

    Diego Silva

  7. University of Lisbon, Lisbon, Portugal

    Catarina Magro

  8. Sentimonitor, Porto Alegre, Brazil

    Hugo Pinto

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Barbero, C. (2022). CQL Grammars for Lexical and Semantic Information Extraction for Portuguese and Italian. In: Pinheiro, V., et al. Computational Processing of the Portuguese Language. PROPOR 2022. Lecture Notes in Computer Science(), vol 13208. Springer, Cham. https://doi.org/10.1007/978-3-030-98305-5_35

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  • DOI: https://doi.org/10.1007/978-3-030-98305-5_35

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