Temporal Information Annotation: Crowd vs. Experts

Rachele Sprugnoli, Tommaso Caselli, Oana Inel

Risultato della ricerca: Contributo in libroContributo a convegno

2 Citazioni (Scopus)

Abstract

This paper describes two sets of crowdsourcing experiments on temporal information annotation conducted on two languages, ie, English and Italian. The first experiment, launched on the CrowdFlower platform, was aimed at classifying temporal relations given target entities. The second one, relying on the CrowdTruth metric, consisted in two subtasks: one devoted to the recognition of events and temporal expressions and one to the detection and classification of temporal relations. The outcomes of the experiments suggest a valuable use of crowdsourcing annotations also for a complex task like Temporal Processing.
Lingua originaleEnglish
Titolo della pubblicazione ospiteProceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)
Pagine3502-3609
Numero di pagine108
Stato di pubblicazionePubblicato - 2016
EventoTenth International Conference on Language Resources and Evaluation (LREC 2016) - Portorož, Slovenia
Durata: 23 mag 201628 mag 2016

Convegno

ConvegnoTenth International Conference on Language Resources and Evaluation (LREC 2016)
CittàPortorož, Slovenia
Periodo23/5/1628/5/16

Keywords

  • Corpus
  • Crowdsourcing
  • Temporal Information Processing

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