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Wiktionary: A new rival for expert-built lexicons? Exploring the possibilities of collaborative lexicography

Summary

The chapter examines whether an online dictionary compiled by volunteers can compete with lexicons produced by professional lexicographers. The authors study Wiktionary, the largest open wiki-based dictionary. They first describe its history, multilingual architecture, macro- and microstructure, and how its community collaborates. The microstructure covers etymology, pronunciation, morphology, semantic relations, and translations. The English, German, and Russian editions of Wiktionary are then compared quantitatively and qualitatively with several expert-built dictionaries. The comparison covers terms, lexemes, word senses, subject domains, and registers. The English edition covers a very large number of terms, while the German and Russian editions are on a par with the expert resources. Neologisms and basic vocabulary are especially well represented in Wiktionary. The dictionaries overlap little with one another, so Wiktionary substantially complements other sources. At the same time, it contains incorrect or overly vague definitions, and it has no formal review procedure. The work provides a systematic description of a resource widely used in NLP. The authors conclude that collaborative lexicography does not replace traditional lexicography but offers it a new perspective.

Key points

  • The English Wiktionary was launched on 12 December 2002 as a companion project to Wikipedia. In August 2010 there were more than 170 language editions, 145 of them active. The English and French editions each had more than 1.6 million entries, and all editions together had more than 9 million.
  • Three editions were chosen for the comparison: English, German, and Russian. The Russian edition was parsed with the Wikokit tool developed by A. A. Krizhanovsky.
  • Wiktionary contains more polysemous lexemes than the expert dictionaries. The order in which entries are created shows what users actually need.
  • Domain labels reveal a bias: the natural sciences, computer science, and leisure are well represented, whereas the social sciences and humanities are poorly covered.
  • Wiktionary is already used in NLP tasks: information retrieval, semantic relatedness computation, and speech synthesis. The entire editing history is public, so it can be used to study the dictionary-making process itself. Entries imported from Webster 1913 are kept separately so that the community can review them.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Cite

Cite as Christian M. Meyer and Iryna Gurevych. 2012. Wiktionary: A new rival for expert-built lexicons? Exploring the possibilities of collaborative lexicography. S. Granger, M. Paquot (eds.), Electronic Lexicography. Oxford University Press, 2012, pp. 259–291.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.1093/acprof:oso/9780199654864.003.0013

@inproceedings{meyer2012wiktionary,
  title = {{Wiktionary: A new rival for expert-built lexicons? Exploring the possibilities of collaborative lexicography}},
  author = {Christian M. Meyer and Iryna Gurevych},
  booktitle = {S. Granger, M. Paquot (eds.), Electronic Lexicography. Oxford University Press, 2012, pp. 259–291},
  year = {2012},
  doi = {10.1093/acprof:oso/9780199654864.003.0013},
  url = {https://doi.org/10.1093/acprof:oso/9780199654864.003.0013}
}

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