This project evaluates four mainstream taggers on a representative collection of child-adult’s dialogues from Child Language Data Exchange System. The nine children’s files from Valian corpora and part of Eve corpora have been manually labeled, and rewrote with LARC tagset. They served as gold standard corpora in the training and testing process. Four taggers: CLAN MOR tagger, ACOPOST trigram tagger, Stanford parser, and Ver. 1.14 of Brill tagger have been tested by 10-fold cross validation. By analyzing what kinds of assumptions the tagger made about category assignment lead to failing, we identify several problematic cases of tagging. By comparing the average error rate of each tagger, we found the size of training data set, and the length of utterance both plays a role to effect tagging accuracy.
","abstract_html":"<p>This project evaluates four mainstream taggers on a representative collection of child-adult’s dialogues from Child Language Data Exchange System. The nine children’s files from Valian corpora and part of Eve corpora have been manually labeled, and rewrote with LARC tagset. They served as gold standard corpora in the training and testing process. Four taggers: CLAN MOR tagger, ACOPOST trigram tagger, Stanford parser, and Ver. 1.14 of Brill tagger have been tested by 10-fold cross validation. By analyzing what kinds of assumptions the tagger made about category assignment lead to failing, we identify several problematic cases of tagging. By comparing the average error rate of each tagger, we found the size of training data set, and the length of utterance both plays a role to effect tagging accuracy.</p>","abstract_has_math":false,"creators":["Huang, Rui"],"institution":"The Graduate School and University Center of The City University of New York","degree_name":"Master of Arts","degree_level":"Master","degree_discipline":"Linguistics","degree_department":null,"school":null,"contributors":[],"advisors":["William Gregory Sakas"],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-09-30T07:00:00Z","date_published":"2016-09-30T07:00:00Z","updated_at":"2026-07-24T02:00:35Z","subjects":["Computational Linguistics","First and Second Language Acquisition","Part-of-speech","Tagger","Tagging","MLU","Tagging Accuracy"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://academicworks.cuny.edu/gc_etds/1577","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["William Gregory Sakas"]},{"key":"dc:creator","label":"Author","values":["Huang, Rui"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-09-14T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Linguistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Master"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Arts"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The Graduate School and University Center of The City University of New York"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computational Linguistics","First and Second Language Acquisition","Part-of-speech","Tagger","Tagging","MLU","Tagging Accuracy"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://academicworks.cuny.edu/gc_etds/1577"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This project evaluates four mainstream taggers on a representative collection of child-adult’s dialogues from Child Language Data Exchange System. The nine children’s files from Valian corpora and part of Eve corpora have been manually labeled, and rewrote with LARC tagset. They served as gold standard corpora in the training and testing process. Four taggers: CLAN MOR tagger, ACOPOST trigram tagger, Stanford parser, and Ver. 1.14 of Brill tagger have been tested by 10-fold cross validation. By analyzing what kinds of assumptions the tagger made about category assignment lead to failing, we identify several problematic cases of tagging. By comparing the average error rate of each tagger, we found the size of training data set, and the length of utterance both plays a role to effect tagging accuracy.
"]},{"key":"dc:title","label":"Title","values":["An Evaluation of POS Taggers for the CHILDES Corpus"]}]}],"canonical_facts":{"dc:contributor.advisor":["William Gregory Sakas"],"dc:creator":["Huang, Rui"],"dc:date.available":["2016-09-14T07:00:00Z"],"dc:description.abstract":["This project evaluates four mainstream taggers on a representative collection of child-adult’s dialogues from Child Language Data Exchange System. The nine children’s files from Valian corpora and part of Eve corpora have been manually labeled, and rewrote with LARC tagset. They served as gold standard corpora in the training and testing process. Four taggers: CLAN MOR tagger, ACOPOST trigram tagger, Stanford parser, and Ver. 1.14 of Brill tagger have been tested by 10-fold cross validation. By analyzing what kinds of assumptions the tagger made about category assignment lead to failing, we identify several problematic cases of tagging. By comparing the average error rate of each tagger, we found the size of training data set, and the length of utterance both plays a role to effect tagging accuracy.
"],"dc:identifier":["https://academicworks.cuny.edu/gc_etds/1577"],"dc:subject":["Computational Linguistics","First and Second Language Acquisition","Part-of-speech","Tagger","Tagging","MLU","Tagging Accuracy"],"dc:title":["An Evaluation of POS Taggers for the CHILDES Corpus"],"thesis:degree_discipline":["Linguistics"],"thesis:degree_level":["Master"],"thesis:degree_name":["Master of Arts"],"thesis:institution_name":["The Graduate School and University Center of The City University of New York"]},"updated_at":"2026-07-24T02:00:35Z"}