A Novel Method for Evaluation of Morphological Segmentation

Javad Nouri, Roman Yangarber

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Unsupervised learning of morphological segmentation of words in a language, based only on a large corpus of words, is a challenging task. Evaluation of the learned segmentations is a challenge in itself, due to the inherent ambiguity of the segmentation task. There is no way to posit unique “correct” segmentation for a set of data in an objective way. Two models may arrive at different ways of segmenting the data, which may nonetheless both be valid. Several evaluation methods have been proposed to date, but they do not insist on consistency of the evaluated model. We introduce a new evaluation methodology, which enforces correctness of segmentation boundaries while also assuring consistency of segmentation decisions across the corpus.
Original languageEnglish
Title of host publicationLREC 2016, Tenth International Conference on Language Resources and Evaluation
EditorsNicoletta Calzolari , Khalid Choukri, Thierry Declerck, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Number of pages9
Place of PublicationParis
PublisherEuropean Language Resources Association (ELRA)
Publication date2016
ISBN (Electronic)978-2-9517408-9-1
Publication statusPublished - 2016
MoE publication typeA4 Article in conference proceedings
EventInternational Conference on Language Resources and Evaluation - Portorož, Slovenia
Duration: 23 May 201628 May 2016
Conference number: 10

Fields of Science

  • 113 Computer and information sciences

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