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The Stanford CoreNLP Natural Language Processing Toolkit
- Christopher D. Manning, M. Surdeanu, John Bauer, J. Finkel, Steven Bethard, David McClosky
- Computer ScienceACL
- 1 June 2014
TLDR
Effective Self-Training for Parsing
- David McClosky, Eugene Charniak, Mark Johnson
- Computer ScienceNAACL
- 4 June 2006
We present a simple, but surprisingly effective, method of self-training a two-phase parser-reranker system using readily available unlabeled data. We show that this type of bootstrapping is possible…
Reranking and Self-Training for Parser Adaptation
- David McClosky, Eugene Charniak, Mark Johnson
- Computer ScienceACL
- 17 July 2006
TLDR
Improving Unsupervised Dependency Parsing with Richer Contexts and Smoothing
- William P. Headden, Mark Johnson, David McClosky
- Computer ScienceNAACL
- 31 May 2009
TLDR
The Role of Context Types and Dimensionality in Learning Word Embeddings
- Oren Melamud, David McClosky, Siddharth Patwardhan, Mohit Bansal
- Computer ScienceNAACL
- 5 January 2016
We provide the first extensive evaluation of how using different types of context to learn skip-gram word embeddings affects performance on a wide range of intrinsic and extrinsic NLP tasks. Our…
Event Extraction as Dependency Parsing
- David McClosky, M. Surdeanu, Christopher D. Manning
- Computer ScienceACL
- 19 June 2011
TLDR
Improving Statistical MT through Morphological Analysis
- S. Goldwater, David McClosky
- Computer Science, LinguisticsHLT
- 6 October 2005
TLDR
Automatic Domain Adaptation for Parsing
- David McClosky, Eugene Charniak, Mark Johnson
- Computer ScienceNAACL
- 2 June 2010
TLDR
Model Combination for Event Extraction in BioNLP 2011
- S. Riedel, David McClosky, M. Surdeanu, A. McCallum, Christopher D. Manning
- Computer ScienceBioNLP@ACL
- 24 June 2011
TLDR
Any domain parsing: automatic domain adaptation for natural language parsing
- Eugene Charniak, David McClosky
- Computer Science
- 2010
TLDR
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