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» A Maximum Entropy Model for Prepositional Phrase Attachment
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EMNLP
2004
13 years 6 months ago
NP Bracketing by Maximum Entropy Tagging and SVM Reranking
We perform Noun Phrase Bracketing by using a local, maximum entropy-based tagging model, which produces bracketing hypotheses. These hypotheses are subsequently fed into a reranki...
Hal Daumé III, Daniel Marcu
NAACL
2010
13 years 3 months ago
A Direct Syntax-Driven Reordering Model for Phrase-Based Machine Translation
This paper presents a direct word reordering model with novel syntax-based features for statistical machine translation. Reordering models address the problem of reordering source...
Niyu Ge
ICML
2004
IEEE
14 years 6 months ago
Learning random walk models for inducing word dependency distributions
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
Kristina Toutanova, Christopher D. Manning, Andrew...
ACL
2009
13 years 3 months ago
Discriminative Approach to Predicate-Argument Structure Analysis with Zero-Anaphora Resolution
This paper presents a predicate-argument structure analysis that simultaneously conducts zero-anaphora resolution. By adding noun phrases as candidate arguments that are not only ...
Kenji Imamura, Kuniko Saito, Tomoko Izumi
ANLP
2000
97views more  ANLP 2000»
13 years 6 months ago
Trainable Methods for Surface Natural Language Generation
We present three systems for surface natural language generation that are trainable from annotated corpora. The first two systems, called NLG1 and NLG2, require a corpus marked on...
Adwait Ratnaparkhi