Grace Ngai


2009

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Proceedings of the ACL-IJCNLP 2009 Student Research Workshop
Brian Roark | Grace Ngai | Davis Muhajereen D. Dimalen | Jenny Rose Finkel | Blaise Thomson
Proceedings of the ACL-IJCNLP 2009 Student Research Workshop

2007

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A Knowledge-Based Approach for Unsupervised Chinese Coreference Resolution
Grace Ngai | Chi-Shing Wang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 12, Number 4, December 2007: Special Issue on Speech and Language Processing for Taiwanese Minnan, Hakka, and Mandarin

2006

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A Clustering Approach for Unsupervised Chinese Coreference Resolution
Chi-shing Wang | Grace Ngai
Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing

2004

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Why Nitpicking Works: Evidence for Occam’s Razor in Error Correctors
Dekai Wu | Grace Ngai | Marine Carpuat
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

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Raising the Bar: Stacked Conservative Error Correction Beyond Boosting
Dekai Wu | Grace Ngai | Marine Carpuat
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Semantic role labeling with Boosting, SVMs, Maximum Entropy, SNOW, and Decision Lists
Grace Ngai | Dekai Wu | Marine Carpuat | Chi-Shing Wang | Chi-Yung Wang
Proceedings of SENSEVAL-3, the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text

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Joining forces to resolve lexical ambiguity: East meets West in Barcelona
Richard Wicentowski | Grace Ngai | Dekai Wu | Marine Carpuat | Emily Thomforde | Adrian Packel
Proceedings of SENSEVAL-3, the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text

2003

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A Stacked, Voted, Stacked Model for Named Entity Recognition
Dekai Wu | Grace Ngai | Marine Carpuat
Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003

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Combining Optimal Clustering and Hidden Markov Models for Extractive Summarization
Pascale Fung | Grace Ngai | Chi-Shun Cheung
Proceedings of the ACL 2003 Workshop on Multilingual Summarization and Question Answering

2002

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Boosting for Named Entity Recognition
Dekai Wu | Grace Ngai | Marine Carpuat | Jeppe Larsen | Yongsheng Yang
COLING-02: The 6th Conference on Natural Language Learning 2002 (CoNLL-2002)

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Identifying Concepts Across Languages: A First Step towards a Corpus-based Approach to Automatic Ontology Alignment
Grace Ngai | Marine Carpuat | Pascale Fung
COLING 2002: The 19th International Conference on Computational Linguistics

2001

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Multidimensional transformation-based learning
Radu Florian | Grace Ngai
Proceedings of the ACL 2001 Workshop on Computational Natural Language Learning (ConLL)

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Inducing Multilingual Text Analysis Tools via Robust Projection across Aligned Corpora
David Yarowsky | Grace Ngai | Richard Wicentowski
Proceedings of the First International Conference on Human Language Technology Research

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Transformation Based Learning in the Fast Lane
Grace Ngai | Radu Florian
Second Meeting of the North American Chapter of the Association for Computational Linguistics

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Inducing Multilingual POS Taggers and NP Bracketers via Robust Projection Across Aligned Corpora
David Yarowsky | Grace Ngai
Second Meeting of the North American Chapter of the Association for Computational Linguistics

2000

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Coaxing Confidences from an Old Freind: Probabilistic Classifications from Transformation Rule Lists
Radu Florian | John C. Henderson | Grace Ngai
2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora

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Rule Writing or Annotation: Cost-efficient Resource Usage for Base Noun Phrase Chunking
Grace Ngai | David Yarowsky
Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics

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Automatic Grammar Induction: Combining, Reducing and Doing Nothing
Eric Brill | John C. Henderson | Grace Ngai
Proceedings of the Sixth International Workshop on Parsing Technologies

This paper surveys three research directions in parsing. First, we look at methods for both automatically generating a set of diverse parsers and combining the outputs of different parsers into a single parse. Next, we will discuss a parsing method known as transformation-based parsing. This method, though less accurate than the best current corpus-derived parsers, is able to parse quite accurately while learning only a small set of easily understood rules, as opposed to the many-megabyte parameter files learned by other techniques. Finally, we review a recent study exploring how people and machines compare at the task of creating a program to automatically annotate noun phrases.

1999

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Man vs. Machine: A Case Study in Base Noun Phrase Learning
Eric Brill | Grace Ngai
Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics