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dc.contributor.authorVatri, Aen
dc.contributor.authorMcGillivray, Barbaraen
dc.date.accessioned2020-08-03T23:31:22Z
dc.date.available2020-08-03T23:31:22Z
dc.date.issued2020-01-01en
dc.identifier.issn1566-5844
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/308728
dc.description.abstractThis short article presents the result of accuracy tests for currently available Ancient Greek lemmatizers and recently published lemmatized corpora. We ran a blinded experiment in which three highly proficient readers of Ancient Greek evaluated the output of the CLTK lemmatizer, of the CLTK backoff lemmatizer, and of GLEM, together with the lemmatizations offered by the Diorisis corpus and the Lemmatized Ancient Greek Texts repository. The texts chosen for this experiment are Homer, Iliad 1.1–279 and Lysias 7. The results suggest that lemmatization methods using large lexica as well as part-of-speech tagging—such as those employed by the Diorisis corpus and the CLTK backoff lemmatizer—are more reliable than methods that rely more heavily on machine learning and use smaller lexica.
dc.publisherBrill
dc.rightsAll rights reserved
dc.rights.uri
dc.titleLemmatization for ancient Greek: An experimental assessment of the state of the arten
dc.typeArticle
prism.endingPage196
prism.issueIdentifier2en
prism.publicationDate2020en
prism.publicationNameJournal of Greek Linguisticsen
prism.startingPage179
prism.volume20en
dc.identifier.doi10.17863/CAM.55817
dcterms.dateAccepted2020-07-29en
rioxxterms.versionofrecord10.1163/15699846-02002001en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2020-01-01en
dc.contributor.orcidMcGillivray, Barbara [0000-0003-3426-8200]
dc.identifier.eissn1569-9846
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idAlan Turing Institute (EP/N510129/1)
cam.orpheus.counter24*
rioxxterms.freetoread.startdate2023-08-03


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