MultiBooked_Corpora [research data]

DOI

We release two corpora of hotel reviews annotated for aspect-level sentiment analysis in Catalan and Basque. We also include scripts which allow the conversion to sentence-level annotations and provide benchmarks for opinion holder, target, and expression extraction based on conditional random fields.

The corpora are compiled from hotel reviews taken mainly from booking.com. The corpora are in Kaf/Naf format [https://github.com/opener-project/kaf/wiki/KAF-structure-overview] [https://github.com/newsreader/NAF], which is an xml-style stand-off format that allows for multiple layers of annotation. Each review was sentence- and word-tokenized and lemmatized using Freeling [http://nlp.lsi.upc.edu/freeling/node/1] for Catalan and ixa-pipes [http://ixa2.si.ehu.es/ixa-pipes/] for Basque. Finally, for each language two annotators annotated opinion holders, opinion targets, and opinion expressions for each review, following the guidelines set out in the OpeNER project [http://www.opener-project.eu/]. Details can be found in the paper. This package includes the two corpora, as well as providing scripts to obtain corpus statistics (corpus_stats.py), reproduce the benchmarks reported in the paper (crf.py), extract only the opinionated units from the text (extract_opinions.py), or map the aspect-level annotations to sentence- or document-level annotated corpora (extract_sentences.py). Requirements for stats and extraction: Python 3, NumPy

Identifier
DOI https://doi.org/10.34810/data398
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/data398
Provenance
Creator Barnes, Jeremy
Publisher CORA.Repositori de Dades de Recerca
Publication Year 2022
Rights Custom Dataset Terms; info:eu-repo/semantics/openAccess; https://dataverse.csuc.cat/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.34810/data398
OpenAccess true
Representation
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Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences