FANDOM


  • coreference resolution: Phrase Detectives (Chamberlain et al., 2008;[1] Chamberlain et al., 2009[2]) was meant to gather a corpus with
  • textual entailment: Negri et al. (2011)[3] (multilingual)
  • semantic role labeling: Hong and Baker (2011)[4], Baker (2012)[5]


Verbosity (Von Ahn et al., 2006)[6] was one of the first attempts in gathering annotations with a GWAP.

Snow et al. (2008)[7] described design and evaluation guidelines for five natural language micro-tasks. However, they explicitly chose a set of tasks that could be easily understood by non-expert contributors, thus leaving the recruitment and training issues open.

References Edit

  1. Jon Chamberlain, Massimo Poesio, and Udo Kruschwitz. 2008. Phrase detec- tives: A web-based collaborative annotation game. Proceedings of I-Semantics, Graz.
  2. Jon Chamberlain, Udo Kruschwitz, and Massimo Poesio. 2009. Constructing an anaphorically annotated corpus with non-experts: Assessing the quality of collaborative annotations. In Proceedings of the 2009 Workshop on The Peo- ple’s Web Meets NLP: Collaboratively Constructed Semantic Resources, pages 57–62. Association for Computational Linguistics.
  3. Matteo Negri, Luisa Bentivogli, Yashar Mehdad, Danilo Giampiccolo, and Alessan- dro Marchetti. 2011. Divide and conquer: crowd- sourcing the creation of cross-lingual textual entail- ment corpora. In Proceedings of the Conference on Empirical Methods in Natural Language Process- ing, EMNLP ’11, pages 670–679, Stroudsburg, PA, USA. Association for Computational Linguistics.
  4. Jisup Hong and Collin F Baker. 2011. How good is the crowd at “real” wsd? ACL HLT 2011, page 30.
  5. Collin F Baker. 2012. Framenet, current collaborations and future goals. Language Re- sources and Evaluation, pages 1–18.
  6. Luis Von Ahn, Mihir Kedia, and Manuel Blum. 2006. Verbosity: a game for col- lecting common-sense facts. In Proceedings of the SIGCHI conference on Human Factors in computing systems, pages 75–78. ACM.
  7. Rion Snow, Brendan O’Connor, Daniel Jurafsky, and Andrew Y Ng. 2008. Cheap and fast—but is it good?: evaluating non-expert an- notations for natural language tasks. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 254–263. Association for Computational Linguistics.