A Multi-lingual Annotated Dataset for Aspect-Oriented Opinion Mining

نویسندگان

  • Salud M. Jiménez Zafra
  • Giacomo Berardi
  • Andrea Esuli
  • Diego Marcheggiani
  • Maria Teresa Martín-Valdivia
  • Alejandro Moreo
چکیده

We present the Trip-MAML dataset, a Multi-Lingual dataset of hotel reviews that have been manually annotated at the sentence-level with Multi-Aspect sentiment labels. This dataset has been built as an extension of an existent English-only dataset, adding documents written in Italian and Spanish. We detail the dataset construction process, covering the data gathering, selection, and annotation. We present inter-annotator agreement figures and baseline experimental results, comparing the three languages. Trip-MAML is a multi-lingual dataset for aspect-oriented opinion mining that enables researchers (i) to face the problem on languages other than English and (ii) to the experiment the application of cross-lingual learning meth-

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تاریخ انتشار 2015