1996 AMaximumEntropyModelForPOS

• (Ratnaparkhi, 1996) ⇒ Adwait Ratnaparkhi. (1996). “A Maximum Entropy Model for Part-of-Speech Tagging.” In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 1996).

Subject Headings: Part-of-Speech Tagging Algorithm, Maximum-Entropy Model.

Cited By

• ~613 http://scholar.google.com/scholar?cites=1354692983594642600

2003

• (Collins, 2003) ⇒ Michael Collins. (2003). “Head-Driven Statistical Models for Natural Language Parsing.” In: Computational Linguistics, 29(4). doi:10.1162/089120103322753356.

2001

• (Lafferty et al., 2001) ⇒ John D. Lafferty, Andrew McCallum, and Fernando Pereira. (2001). “Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data.” In: Proceedings of ICML Conference (ICML 2001).

Quotes

Abstract

This paper presents a statistical model which trains from a corpus annotated with Part-Of-Speech tags and assigns them to previously unseen text with state-of-the-art accuracy (96.6%). The model can be classified as a Maximum Entropy model and simultaneously uses many contextual "features" to predict the POS tag. Furthermore, this paper demonstrates the use of specialized features to model difficult tagging decisions, discusses the corpus consistency problems discovered during the implementation of these features, and proposes a training strategy that mitigates these problems.

References

• …
• (Darroch & Ratcliff, 1972) ⇒ John N. Darroch, and Douglas Ratcliff. (1972). “Generalized Iterative Scaling for Log-Linear Models.” In: The Annals of Mathematical Statistics, 43(5).
• …,

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1996 AMaximumEntropyModelForPOS	Adwait Ratnaparkhi			A Maximum Entropy Model for Part-of-Speech Tagging		Proceedings of the Conference on Empirical Methods in Natural Language Processing	http://acl.ldc.upenn.edu/W/W96/W96-0213.pdf			1996