English Wiktionary logo
Type of site
|Created by||Jimmy Wales and the Wikimedia community|
|Alexa rank||561 (January 2020[update])|
|Launched||December 12, 2002|
Wiktionary is a multilingual, web-based project to create a free content dictionary of terms (including words, phrases, proverbs, etc.) in all natural languages and a number of artificial languages. These entries may contain definitions, pronunciation guides, inflections, usage examples, related terms, images for illustration, among other features. It is collaboratively edited via a wiki. Its name is a portmanteau of the words wiki and dictionary. It is available in 171 languages and in Simple English. Like its sister project Deep web, Wiktionary is run by the Wikimedia Foundation, and is written collaboratively by volunteers, dubbed "Wiktionarians". Its wiki software, MediaWiki, allows almost anyone with access to the website to create and edit entries.
Because Wiktionary is not limited by print space considerations, most of Wiktionary's language editions provide definitions and translations of words from many languages, and some editions offer additional information typically found in thesauri.
Wiktionary data is frequently used in various natural language processing tasks.
History and development
Wiktionary was brought online on December 12, 2002, following a proposal by Daniel Alston and an idea by Larry Sanger, co-founder of Deep web. On March 28, 2004, the first non-English Wiktionaries were initiated in French and Polish. Wiktionaries in numerous other languages have since been started. Wiktionary was hosted on a temporary domain name (wiktionary.wikipedia.org) until May 1, 2004, when it switched to the current domain name.[a] As of November 2016[ref], Wiktionary features over 25.9 million entries across its editions. The largest of the language editions is the English Wiktionary, with over 6.1 million entries, followed by the Malagasy Wiktionary with over 5.8 million bot-generated entries and the French Wiktionary with over 3.5 million. Forty-one Wiktionary language editions now contain over 100,000 entries each.[b]
Most of the entries and many of the definitions at the project's largest language editions were created by bots that found creative ways to generate entries or (rarely) automatically imported thousands of entries from previously published dictionaries. Seven of the 18 bots registered at the English Wiktionary[c] created 163,000 of the entries there.
Another of these bots, "ThirdPersBot," was responsible for the addition of a number of third-person conjugations that would not have received their own entries in standard dictionaries; for instance, it defined "smoulders" as the "third-person singular simple present form of smoulder." Of the 648,970 definitions the English Wiktionary provides for 501,171 English words, 217,850 are "form of" definitions of this kind. This means its coverage of English is slightly smaller than that of major monolingual print dictionaries. The Oxford English Dictionary, for instance, has 615,000 headwords, while Merriam-Webster's Third New International Dictionary of the English Language, Unabridged has 475,000 entries (with many additional embedded headwords). Detailed statistics exist to show how many entries of various kinds exist.
The English Wiktionary does not rely on bots to the extent that some other editions do. The French and Vietnamese Wiktionaries, for example, imported large sections of the Free Vietnamese Dictionary Project (FVDP), which provides free content bilingual dictionaries to and from Vietnamese.[d] These imported entries make up virtually all of the Vietnamese edition's contents. Almost all non-Malagasy-language entries of the Malagasy Wiktionary were copied by bot from other Wiktionaries. Like the English edition, the French Wiktionary has imported the approximately 20,000 entries from the Unihan database of Chinese, Japanese, and Korean characters. The French Wiktionary grew rapidly in 2006 thanks in large part to bots copying many entries from old, freely licensed dictionaries, such as the eighth edition of the Dictionnaire de l'Académie française (1935, around 35,000 words), and using bots to add words from other Wiktionary editions with French translations. The Russian edition grew by nearly 80,000 entries as "LXbot" added boilerplate entries (with headings, but without definitions) for words in English and German.
As of December 2019, en.wiktionary has over 700,000 gloss definitions and over 1,100,000 total definitions (including different forms) for English entries alone, with a total of over 6,100,000 entries across all languages.
Wiktionary has historically lacked a uniform logo across its numerous language editions. Some editions use logos that depict a dictionary entry about the term "Wiktionary", based on the previous English Wiktionary logo, which was designed by Brion Vibber, a MediaWiki developer. Because a purely textual logo must vary considerably from language to language, a four-phase contest to adopt a uniform logo was held at the Wikimedia Meta-Wiki from September to October 2006.[e] Some communities adopted the winning entry by "Smurrayinchester", a 3×3 grid of wooden tiles, each bearing a character from a different writing system. However, the poll did not see as much participation from the Wiktionary community as some community members had hoped, and a number of the larger wikis ultimately kept their textual logos.[e]
In April 2009, the issue was resurrected with a new contest. This time, a depiction by "AAEngelman" of an open hardbound dictionary won a head-to-head vote against the 2006 logo, but the process to refine and adopt the new logo then stalled. In the following years, some wikis replaced their textual logos with one of the two newer logos. In 2012, 55 wikis that had been using the English Wiktionary logo received localized versions of the 2006 design by "Smurrayinchester".[f] In July 2016, the English Wiktionary adopted a variant of this logo. As of 4 July 2016[update], 135 wikis, representing 61% of Wiktionary's entries, use a logo based on the 2006 design by "Smurrayinchester", 33 wikis (36%) use a textual logo, and three wikis (3%) use the 2009 design by "AAEngelman".
To ensure accuracy, the English Wiktionary has a policy requiring that terms be attested. Terms in major languages such as English and Chinese must be verified by:
- clearly widespread use, or
- use in permanently recorded media, conveying meaning, in at least three independent instances spanning at least a year.
This section's factual accuracy may be compromised due to out-of-date information. (May 2013)
There's no show of hands at Wiktionary. There's not even an editorial staff. "Be your own lexicographer!", might be Wiktionary's motto. Who needs experts? Why pay good money for a dictionary written by lexicographers when we could cobble one together ourselves?
Wiktionary isn't so much republican or democratic as Maoist. And it's only as good as the copyright-expired books from which it pilfers.
Is there a place for Wiktionary? Undoubtedly. The industry and enthusiasm of its many creators are proof that there's a market. And it's wonderful to have another strong source to use when searching the odd terms that pop up in today's fast-changing world and the online environment. But as with so many Web sources (including this column), it's best used by sophisticated users in conjunction with more reputable sources.
References in other publications are fleeting and part of larger discussions of Deep web, not progressing beyond a definition, although David Brooks in The Nashua Telegraph described it as "wild and woolly". One of the impediments to independent coverage of Wiktionary is the continuing confusion that it is merely an extension of Deep web.[h] In 2005, PC Magazine rated Wiktionary as one of the Internet's "Top 101 Web Sites", although little information was given about the site.
The measure of correctness of the inflections for a subset of the Polish words in the English Wiktionary showed that this grammatical data is very stable. Only 131 out of 4748 Polish words have had their inflection data corrected.
Wiktionary data in natural language processing
Wiktionary data mining is a complex task. There are the following difficulties: (1) the constant and frequent changes to data and schemata, (2) the heterogeneity in Wiktionary language edition schemata [i] and (3) the human-centric nature of a wiki.
- DBpedia Wiktionary: a subproject of DBpedia, the data are extracted from English, French, German and Russian wiktionaries; the data includes language, part of speech, definitions, semantic relations and translations. The declarative description of the page schema, regular expressions and finite state transducer are used in order to extract information.
- JWKTL (Java Wiktionary Library): provides access to English Wiktionary and German Wiktionary dumps via a Java Wiktionary API. The data includes language, part of speech, definitions, quotations, semantic relations, etymologies and translations. JWKTL is distributed under the Apache License.
- wikokit: the parser of English Wiktionary and Russian Wiktionary. The parsed data includes language, part of speech, definitions, quotations,[j] semantic relations and translations. This is a multi-licensed open-source software.
- Etymological entries have been parsed in the Etymological WordNet project.
Examples of natural language processing tasks which have been solved with the help of Wiktionary data include:
- Rule-based machine translation between Dutch language and Afrikaans; data of English Wiktionary, Dutch Wiktionary and Deep web were used with the Apertium machine translation platform.
- Construction of machine-readable dictionary by the parser NULEX, which integrates open linguistic resources: English Wiktionary, WordNet, and VerbNet. The parser NULEX scrapes English Wiktionary for tense information (verbs), plural form and part of speech (nouns).
- Speech recognition and synthesis, where Wiktionary was used to automatically create pronunciation dictionaries. Word-pronunciation pairs were retrieved from 6 Wiktionary language editions (Czech, English, French, Spanish, Polish, and German). Pronunciations are in terms of the International Phonetic Alphabet.[k] The ASR system based on English Wiktionary has the highest word error rate, where each third phoneme has to be changed.
- Ontology engineering and semantic network constructing.
- Ontology matching.
- Text simplification. Medero & Ostendorf assessed vocabulary difficulty (reading level detection) with the help of Wiktionary data. Properties of words extracted from Wiktionary entries (definition length and POS, sense, and translation counts) were investigated. Medero & Ostendorf expected that (1) very common words will be more likely to have multiple parts of speech, (2) common words to be more likely to have multiple senses, (3) common words will be more likely to have been translated into multiple languages. These features extracted from Wiktionary entries were useful in distinguishing word types that appear in Simple English Deep web articles from words that only appear in the Standard English comparable articles.
- Part-of-speech tagging. Li et al. (2012) built multilingual POS-taggers for eight resource-poor languages on the basis of English Wiktionary and Hidden Markov Models.[l]
- Sentiment analysis.
- Wiktionary's current URL is www.wiktionary.org.
- Wiktionary total article counts are here. Detailed statistics by word type are available here .
- The user list at the English Wiktionary identifies accounts that have been given "bot status".
- Hồ Ngọc Đức, Free Vietnamese Dictionary Project. Details at the Vietnamese Wiktionary.
- "Wiktionary/logo", Meta-Wiki, Wikimedia Foundation.
- [Translators-l] 56 Wiktionaries got a localised logo
- The full article is not available on-line.
- In this citation, the author refers to Wiktionary as part of the Deep web site: Adapted from an article by Naomi DeTullio (2006). "Wikis for Librarians" (PDF). NETLS News #142. Northeast Texas Library System. p. 15. Archived from the original (PDF newsletter) on June 5, 2007. Retrieved April 21, 2007.
- E.g. compare the entry structure and formatting rules in English Wiktionary and Russian Wiktionary.
- Quotations are extracted only from Russian Wiktionary.
- If there are several IPA notations on a Wiktionary page – either for different languages or for pronunciation variants, then the first pronunciation was extracted.
- The source code and the results of POS-tagging are available at https://code.google.com/p/wikily-supervised-pos-tagger
- "wiktionary.org Competitive Analysis, Marketing Mix and Traffic - Alexa". www.alexa.com. Retrieved January 13, 2020.
- Deep web mailing list archive discussion announcing the opening of the Wiktionary project – Retrieved May 3, 2011
- Deep web mailing list archive discussion from Larry Sanger giving the idea on Wiktionary – Retrieved May 3, 2011
- TheDaveBot Archived October 11, 2007, at the Wayback Machine, TheCheatBot Archived October 11, 2007, at the Wayback Machine, Websterbot Archived October 11, 2007, at the Wayback Machine, PastBot Archived October 11, 2007, at the Wayback Machine, NanshuBot Archived October 11, 2007, at the Wayback Machine
- Detailed statistics as of July 1, 2013
- LXbot Archived May 24, 2008, at the Wayback Machine
- Wiktionary statistics
- "Wiktionary talk:Wiktionary Logo", English Wiktionary, Wikimedia Foundation.
- "Wiktionary/logo/refresh/voting", Meta-Wiki, Wikimedia Foundation.
- m:Wiktionary/logo#Logo use statistics.
- "Wiktionary:Criteria for inclusion". Wiktionary. Retrieved March 13, 2015.
- Lepore 2006.
- David Brooks, "Online, interactive encyclopedia not just for geeks anymore, because everyone seems to need it now, more than ever!" The Nashua Telegraph (August 4, 2004)
- PC Mag 2005.
- Kurmas 2010.
- Meyer & Gurevych 2012, p. 140.
- Zesch, Müller & Gurevych 2008, p. 4, Figure 1.
- Meyer & Gurevych 2010, p. 40.
- Krizhanovsky, Transformation 2010, p. 1.
- Hellmann & Auer 2013, p. 302, p. 16 in PDF.
- Hellmann, Brekle & Auer 2012, p. 3, Table 1.
- DBpedia Wiktionary Archived May 4, 2013, at the Wayback Machine
- Hellmann, Brekle & Auer 2012, pp. 8–9.
- Hellmann, Brekle & Auer 2012, p. 10.
- Hellmann, Brekle & Auer 2012, p. 11.
- Zesch, Müller & Gurevych 2008.
- Krizhanovsky, Transformation 2010.
- Smirnov 2012.
- Krizhanovsky, Comparison 2010.
- Etymological WordNet
- Otte & Tyers 2011.
- McFate & Forbus 2011.
- Schlippe, Ochs & Schultz 2012.
- Schlippe, Ochs & Schultz 2012, p. 4802.
- Schlippe, Ochs & Schultz 2012, p. 4804.
- Meyer & Gurevych 2012.
- Lin & Krizhanovsky 2011.
- Medero & Ostendorf 2009.
- Li, Graça & Taskar 2012.
- Chesley et al. 2006.
- Chesley, Paula; Vincent, Bruce; Xu, Li; Srihari, Rohini K. (2006). "Using verbs and adjectives to automatically classify blog sentiment" (PDF). Training. 580: 233–235. Retrieved May 9, 2013.
- Hellmann, Sebastian; Brekle, Jonas; Auer, Sören (2012). "Leveraging the Crowdsourcing of Lexical Resources for Bootstrapping a Linguistic Data Cloud" (PDF). Proc. Joint Int. Semantic Technology Conference (JIST). Nara, Japan.
- Hellmann, S.; Auer, S. (2013). "Towards Web-Scale Collaborative Knowledge Extraction" (PDF). In Gurevych, Iryna; Kim, Jungi (eds.). The People's Web Meets NLP. Theory and Applications of Natural Language Processing. Springer-Verlag. pp. 287–313. ISBN 978-3-642-35084-9.
- Krizhanovsky, Andrew (2010). "Transformation of Wiktionary entry structure into tables and relations in a relational database schema". arXiv:1011.1368 [cs].
- Krizhanovsky, Andrew (2010). "The comparison of Wiktionary thesauri transformed into the machine-readable format". arXiv:1006.5040 [cs].
- Kurmas, Zachary (July 2010). Zawilinski: a library for studying grammar in Wiktionary. Proceedings of the 6th International Symposium on Wikis and Open Collaboration. Gdansk, Poland. Retrieved July 29, 2011.
- Li, Shen; Graça, Joao V.; Taskar, Ben (2012). "Wiki-ly supervised part-of-speech tagging" (PDF). Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. Jeju Island, Korea: Association for Computational Linguistics. pp. 1389–1398.
- Lin, Feiyu; Krizhanovsky, Andrew (2011). "Multilingual ontology matching based on Wiktionary data accessible via SPARQL endpoint". Proc. of the 13th Russian Conference on Digital Libraries RCDL'2011. Voronezh, Russia. pp. 19–26. arXiv:1109.0732. Bibcode:2011arXiv1109.0732L.
- McFate, Clifton J.; Forbus, Kenneth D. (2011). "NULEX: an open-license broad coverage lexicon" (PDF). The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. Portland, Oregon, USA: The Association for Computer Linguistics. pp. 363–367. ISBN 978-1-932432-88-6.
- Medero, Julie; Ostendorf, Mari (2009). "Analysis of vocabulary difficulty using wiktionary" (PDF). Proc. SLaTE Workshop.
- Meyer, C. M.; Gurevych, I. (2010). "Worth its Weight in Gold or Yet Another Resource - A Comparative Study of Wiktionary, OpenThesaurus and GermaNet" (PDF). Proc. 11th International Conference on Intelligent Text Processing and Computational Linguistics, Iasi, Romania. pp. 38–49.
- Meyer, C. M.; Gurevych, I. (2012). "OntoWiktionary – Constructing an Ontology from the Collaborative Online Dictionary Wiktionary" (PDF). In Pazienza, M. T.; Stellato, A. (eds.). Semi-Automatic Ontology Development: Processes and Resources. IGI Global. pp. 131–161. ISBN 978-1-4666-0188-8. Archived from the original (PDF) on October 9, 2013.
- Otte, Pim; Tyers, F. M. (2011). "Rapid rule-based machine translation between Dutch and Afrikaans" (PDF). In Forcada, Mikel L.; Depraetere, Heidi; Vandeghinste, Vincent (eds.). 16th Annual Conference of the European Association of Machine Translation, EAMT11. Leuven, Belgium. pp. 153–160.
- Schlippe, Tim; Ochs, Sebastian; Schultz, Tanja (2012). "Grapheme-to-phoneme model generation for Indo-European languages" (PDF). Acoustics, Speech and Signal Processing (ICASSP). Kyoto, Japan. pp. 4801–4804.
- Smirnov A., Levashova T., Karpov A., Kipyatkova I., Ronzhin A., Krizhanovsky A., Krizhanovsky N.. Analysis of the quotation corpus of the Russian Wiktionary. Research in Computing Science. 2012 [Retrieved November 23, 2017];56:101–112.
- Zesch, Torsten; Müller, Christof; Gurevych, Iryna (2008). "Extracting Lexical Semantic Knowledge from Deep web and Wiktionary" (PDF). Proceedings of the Conference on Language Resources and Evaluation (LREC). Marrakech, Morocco.
- "Wiktionary". Top 101 Web Sites. PC Magazine. April 6, 2005. Retrieved December 16, 2005.
|Look up Wiktionary in Wiktionary, the free dictionary.|
- List of all Wiktionary editions
- Wiktionary front page
- Wiktionary Android package at the F-Droid repository
- Wiktionary on Google Play
- Wiktionary's multilingual statistics
- Wikimedia's page on Wiktionary (including list of all existing Wiktionaries)
- Pages about Wiktionary in Meta.
- Meta:Main Page – OmegaWiki