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SFU ReviewSP-NEG: a Spanish corpus annotated with negation for sentiment analysis. A typology of negation patterns

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Abstract

In this paper, we present SFU ReviewSP-NEG, the first Spanish corpus annotated with negation with a wide coverage freely available. We describe the methodology applied in the annotation of the corpus including the tagset, the linguistic criteria and the inter-annotator agreement tests. We also include a complete typology of negation patterns in Spanish. This typology has the advantage that it is easy to express in terms of a tagset for corpus annotation: the types are clearly defined, which avoids ambiguity in the annotation process, and they provide wide coverage (i.e. they resolved all the cases occurring in the corpus). We use the SFU ReviewSP as a base in order to make the annotations. The corpus consists of 400 reviews, 221,866 words and 9455 sentences, out of which 3022 sentences contain at least one negation structure.

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Notes

  1. Version 1.0.0: http://sinai.ujaen.es/sfu-review-sp-neg-2/.

  2. These sentences were extracted from 730 documents from the DrugBank database (Wishart et al. 2008).

  3. http://www.coli.uni-saarland.de/projects/semeval2010_FG/.

  4. The works are The Hound of the Baskervilles and The Adventure of Wisteria Lodge.

  5. The corpus is available in : http://www.clips.ua.ac.be/BiographTA/corpora.html.

  6. In Bioscope, a very fine-grained analysis of the scope is applied, taking into account very specific cases, for medical domain.

  7. Unified Medical Language System.

  8. NP, PP and ADJP stand for nominal, adjectival and prepositional phrase respectively.

  9. We use indistinctly the term negation particle and negation marker.

  10. In oral language, the focus is often marked with specific intonation (pitch) and intensity (volume).

  11. In the examples, we use brackets to indicate the scope and we underline the event.

  12. As a result of the annotation of the corpus, we built up a lexicon containing the collected set of negation markers and cues.

  13. Sentence extracted from the review: no_2_20.txt–Domain: hotels–SFU Review\(_{SP}\)-NEG.

  14. d = determinant, n = noun, v = verb, a = adjective, r = adverb, c = conjunction, s = preposition, f = punctuation mark.

  15. For instance, <postype=“article”> indicates that the determiner is an article and <complex=“no”> indicates that the preposition is not complex.

  16. For a complete description of the morphological tags, see http://clic.ub.edu/corpus/ancora-documentacio.

  17. http://nlp.lsi.upc.edu/freeling/node/30.

  18. http://annotation.exmaralda.org/index.php/AnCoraPipe.

    User’s guide: http://clic.ub.edu/ca/ancorapipe.

  19. 95.82% of the 4329 negation structures have a semantic value different from “noneg” (Table 5).

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Acknowledgements

This work has been partially supported by a Grant from the Ministerio de Educación, Cultura y Deporte (MECD–scholarship FPU014/00983), Fondo Europeo de Desarrollo Regional (FEDER), and the projects REDES (TIN2015-65136-C2-1-R) and SOMEMBED-SLANG (TIN2015-71147-C2-2), which receive financial support from the Spanish Ministerio de Economía y Competitividad. We would like to thank Maite Taboada and her team for sharing the useful SFU resource with the research community. We would also like to express our gratitude to the three anonymous reviewers for their comments and suggestions for improving this article.

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Authors and Affiliations

  1. Department of Computer Science, Universidad de Jaén, Campus Las Lagunillas, 23071, Jaén, Spain

    Salud María Jiménez-Zafra, M. Teresa Martín-Valdivia & L. Alfonso Ureña-López

  2. CLiC, Centre de Llenguatge i Computació, Department of Linguistics, University of Barcelona, 08007, Barcelona, Spain

    Mariona Taulé & M. Antónia Martí

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  1. Salud María Jiménez-Zafra
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  2. Mariona Taulé
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Correspondence to Salud María Jiménez-Zafra.

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Jiménez-Zafra, S.M., Taulé, M., Martín-Valdivia, M.T. et al. SFU ReviewSP-NEG: a Spanish corpus annotated with negation for sentiment analysis. A typology of negation patterns. Lang Resources & Evaluation 52, 533–569 (2018). https://doi.org/10.1007/s10579-017-9391-x

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