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- Publications
- Influence
Message Understanding Conference- 6: A Brief History
- R. Grishman, B. Sundheim
- Computer Science
- COLING
- 5 August 1996
We have recently completed the sixth in a series of "Message Understanding Conferences" which are designed to promote and evaluate research in information extraction. MUC-6 introduced several… Expand
The NomBank Project: An Interim Report
- Adam Meyers, R. Reeves, +4 authors R. Grishman
- Computer Science
- FCP@NAACL-HLT
- 2004
This paper describes NomBank, a project that will provide argument structure for instances of common nouns in the Penn Treebank II corpus. NomBank is part of a larger effort to add additional layers… Expand
Overview of the TAC 2010 Knowledge Base Population Track
- Huai-zhong Ji, R. Grishman, H. Dang, Kira Griffitt, J. Ellis
- Computer Science
- 2010
In this paper we give an overview of the Knowledge Base Population (KBP) track at TAC 2010. The main goal of KBP is to promote research in discovering facts about entities and expanding a structured… Expand
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Joint Event Extraction via Recurrent Neural Networks
- T. Nguyen, Kyunghyun Cho, R. Grishman
- Computer Science
- HLT-NAACL
- 2016
Event extraction is a particularly challenging problem in information extraction. The stateof-the-art models for this problem have either applied convolutional neural networks in a pipelined… Expand
A Procedure for Quantitatively Comparing the Syntactic Coverage of English Grammars
- E. Black, Steven P. Abney, +12 authors T. Strzalkowski
- Philosophy, Computer Science
- HLT
- 19 February 1991
The problem of quantitatively comparing the performance of different broad-coverage grammars of English has to date resisted solution. Prima facie, known English grammars appear to disagree strongly… Expand
Discovering Relations among Named Entities from Large Corpora
- T. Hasegawa, S. Sekine, R. Grishman
- Computer Science
- ACL
- 21 July 2004
Discovering the significant relations embedded in documents would be very useful not only for information retrieval but also for question answering and summarization. Prior methods for relation… Expand
Relation Extraction: Perspective from Convolutional Neural Networks
- T. Nguyen, R. Grishman
- Computer Science
- VS@HLT-NAACL
- 1 June 2015
Up to now, relation extraction systems have made extensive use of features generated by linguistic analysis modules. Errors in these features lead to errors of relation detection and classification.… Expand
Comlex Syntax: Building a Computational Lexicon
- R. Grishman, C. Macleod, Adam Meyers
- Computer Science
- COLING
- 5 August 1994
We describe the design of Comlex Syntax, a computational lexicon providing detailed syntactic information for approximately 38,000 English headwords. We consider the types of errors which arise in… Expand
A maximum entropy approach to named entity recognition
- R. Grishman, Andrew Borthwick
- Computer Science
- 1999
This thesis describes a novel statistical named-entity (i.e. “proper name”) recognition system known as “MENE” (Maximum Entropy Named Entity). Named entity (N.E.) recognition is a form of information… Expand
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NOMLEX: a lexicon of nominalizations
- C. Macleod, R. Grishman, Adam Meyers, Leslie Barrett, R. Reeves
- Computer Science
- 1998
NOMLEX (NOMinalization LEXicon) is a dictionary of English nominalizations currently under development at New York University. NOMLEX seeks not only to describe the allowed complements for a… Expand
- 140
- 23
- PDF