Ralph Grishman

Also published as: R. Grishman


2021

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Learning Relatedness between Types with Prototypes for Relation Extraction
Lisheng Fu | Ralph Grishman
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Relation schemas are often pre-defined for each relation dataset. Relation types can be related from different datasets and have overlapping semantics. We hypothesize we can combine these datasets according to the semantic relatedness between the relation types to overcome the problem of lack of training data. It is often easy to discover the connection between relation types based on relation names or annotation guides, but hard to measure the exact similarity and take advantage of the connection between the relation types from different datasets. We propose to use prototypical examples to represent each relation type and use these examples to augment related types from a different dataset. We obtain further improvement (ACE05) with this type augmentation over a strong baseline which uses multi-task learning between datasets to obtain better feature representation for relations. We make our implementation publicly available: https://github.com/fufrank5/relatedness

2018

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A Case Study on Learning a Unified Encoder of Relations
Lisheng Fu | Bonan Min | Thien Huu Nguyen | Ralph Grishman
Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text

Typical relation extraction models are trained on a single corpus annotated with a pre-defined relation schema. An individual corpus is often small, and the models may often be biased or overfitted to the corpus. We hypothesize that we can learn a better representation by combining multiple relation datasets. We attempt to use a shared encoder to learn the unified feature representation and to augment it with regularization by adversarial training. The additional corpora feeding the encoder can help to learn a better feature representation layer even though the relation schemas are different. We use ACE05 and ERE datasets as our case study for experiments. The multi-task model obtains significant improvement on both datasets.

2017

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Domain Adaptation for Relation Extraction with Domain Adversarial Neural Network
Lisheng Fu | Thien Huu Nguyen | Bonan Min | Ralph Grishman
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

Relations are expressed in many domains such as newswire, weblogs and phone conversations. Trained on a source domain, a relation extractor’s performance degrades when applied to target domains other than the source. A common yet labor-intensive method for domain adaptation is to construct a target-domain-specific labeled dataset for adapting the extractor. In response, we present an unsupervised domain adaptation method which only requires labels from the source domain. Our method is a joint model consisting of a CNN-based relation classifier and a domain-adversarial classifier. The two components are optimized jointly to learn a domain-independent representation for prediction on the target domain. Our model outperforms the state-of-the-art on all three test domains of ACE 2005.

2016

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Modeling Skip-Grams for Event Detection with Convolutional Neural Networks
Thien Huu Nguyen | Ralph Grishman
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

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Entity Linking with a Paraphrase Flavor
Maria Pershina | Yifan He | Ralph Grishman
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The task of Named Entity Linking is to link entity mentions in the document to their correct entries in a knowledge base and to cluster NIL mentions. Ambiguous, misspelled, and incomplete entity mention names are the main challenges in the linking process. We propose a novel approach that combines two state-of-the-art models ― for entity disambiguation and for paraphrase detection ― to overcome these challenges. We consider name variations as paraphrases of the same entity mention and adopt a paraphrase model for this task. Our approach utilizes a graph-based disambiguation model based on Personalized Page Rank, and then refines and clusters its output using the paraphrase similarity between entity mention strings. It achieves a competitive performance of 80.5% in B3+F clustering score on diagnostic TAC EDL 2014 data.

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A Two-stage Approach for Extending Event Detection to New Types via Neural Networks
Thien Huu Nguyen | Lisheng Fu | Kyunghyun Cho | Ralph Grishman
Proceedings of the 1st Workshop on Representation Learning for NLP

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Joint Event Extraction via Recurrent Neural Networks
Thien Huu Nguyen | Kyunghyun Cho | Ralph Grishman
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2015

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Relation Extraction: Perspective from Convolutional Neural Networks
Thien Huu Nguyen | Ralph Grishman
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing

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Idiom Paraphrases: Seventh Heaven vs Cloud Nine
Maria Pershina | Yifan He | Ralph Grishman
Proceedings of the First Workshop on Linking Computational Models of Lexical, Sentential and Discourse-level Semantics

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Improving Event Detection with Abstract Meaning Representation
Xiang Li | Thien Huu Nguyen | Kai Cao | Ralph Grishman
Proceedings of the First Workshop on Computing News Storylines

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Improving Event Detection with Active Learning
Kai Cao | Xiang Li | Miao Fan | Ralph Grishman
Proceedings of the International Conference Recent Advances in Natural Language Processing

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Improving Event Detection with Dependency Regularization
Kai Cao | Xiang Li | Ralph Grishman
Proceedings of the International Conference Recent Advances in Natural Language Processing

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Jointly Embedding Relations and Mentions for Knowledge Population
Miao Fan | Kai Cao | Yifan He | Ralph Grishman
Proceedings of the International Conference Recent Advances in Natural Language Processing

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Semantic Representations for Domain Adaptation: A Case Study on the Tree Kernel-based Method for Relation Extraction
Thien Huu Nguyen | Barbara Plank | Ralph Grishman
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

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Event Detection and Domain Adaptation with Convolutional Neural Networks
Thien Huu Nguyen | Ralph Grishman
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

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Personalized Page Rank for Named Entity Disambiguation
Maria Pershina | Yifan He | Ralph Grishman
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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ICE: Rapid Information Extraction Customization for NLP Novices
Yifan He | Ralph Grishman
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations

2014

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Proceedings of the COLING Workshop on Synchronic and Diachronic Approaches to Analyzing Technical Language
Adam Meyers | Yifan He | Ralph Grishman
Proceedings of the COLING Workshop on Synchronic and Diachronic Approaches to Analyzing Technical Language

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Jargon-Term Extraction by Chunking
Adam Meyers | Zachary Glass | Angus Grieve-Smith | Yifan He | Shasha Liao | Ralph Grishman
Proceedings of the COLING Workshop on Synchronic and Diachronic Approaches to Analyzing Technical Language

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Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction
Thien Huu Nguyen | Ralph Grishman
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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Infusion of Labeled Data into Distant Supervision for Relation Extraction
Maria Pershina | Bonan Min | Wei Xu | Ralph Grishman
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2013

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An Efficient Active Learning Framework for New Relation Types
Lisheng Fu | Ralph Grishman
Proceedings of the Sixth International Joint Conference on Natural Language Processing

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Distant Supervision for Relation Extraction with an Incomplete Knowledge Base
Bonan Min | Ralph Grishman | Li Wan | Chang Wang | David Gondek
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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A Preliminary Study of Tweet Summarization using Information Extraction
Wei Xu | Ralph Grishman | Adam Meyers | Alan Ritter
Proceedings of the Workshop on Language Analysis in Social Media

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Gathering and Generating Paraphrases from Twitter with Application to Normalization
Wei Xu | Alan Ritter | Ralph Grishman
Proceedings of the Sixth Workshop on Building and Using Comparable Corpora

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Filling Knowledge Base Gaps for Distant Supervision of Relation Extraction
Wei Xu | Raphael Hoffmann | Le Zhao | Ralph Grishman
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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Confidence Estimation for Knowledge Base Population
Xiang Li | Ralph Grishman
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

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Towards Fine-grained Citation Function Classification
Xiang Li | Yifan He | Adam Meyers | Ralph Grishman
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

2012

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Ensemble Semantics for Large-scale Unsupervised Relation Extraction
Bonan Min | Shuming Shi | Ralph Grishman | Chin-Yew Lin
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

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Structural Linguistics and Unsupervised Information Extraction
Ralph Grishman
Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction (AKBC-WEKEX)

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Challenges in the Knowledge Base Population Slot Filling Task
Bonan Min | Ralph Grishman
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

The Knowledge Based Population (KBP) evaluation track of the Text Analysis Conferences (TAC) has been held for the past 3 years. One of the two tasks of KBP is slot filling: finding within a large corpus the values of a set of attributes of given people and organizations. This task has proven very challenging, with top systems rarely exceeding 30% F-measure. In this paper, we present an error analysis and classification for those answers which could be found by a manual corpus search but were not found by any of the systems participating in the 2010 evaluation. The most common sources of failure were limitations on inference, errors in coreference (particularly with nominal anaphors), and errors in named entity recognition. We relate the types of errors to the characteristics of the task and show the wide diversity of problems that must be addressed to improve overall performance.

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Paraphrasing for Style
Wei Xu | Alan Ritter | Bill Dolan | Ralph Grishman | Colin Cherry
Proceedings of COLING 2012

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Compensating for Annotation Errors in Training a Relation Extractor
Bonan Min | Ralph Grishman
Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics

2011

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INVITED TALK 1: The Knowledge Base Population Task: Challenges for Information Extraction
Ralph Grishman
Proceedings of the RANLP 2011 Workshop on Information Extraction and Knowledge Acquisition

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Fine-grained Entity Set Refinement with User Feedback
Bonan Min | Ralph Grishman
Proceedings of the RANLP 2011 Workshop on Information Extraction and Knowledge Acquisition

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Exploiting Syntactic and Distributional Information for Spelling Correction with Web-Scale N-gram Models
Wei Xu | Joel Tetreault | Martin Chodorow | Ralph Grishman | Le Zhao
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

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Using Prediction from Sentential Scope to Build a Pseudo Co-Testing Learner for Event Extraction
Shasha Liao | Ralph Grishman
Proceedings of 5th International Joint Conference on Natural Language Processing

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Passage Retrieval for Information Extraction using Distant Supervision
Wei Xu | Ralph Grishman | Le Zhao
Proceedings of 5th International Joint Conference on Natural Language Processing

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Semi-supervised Relation Extraction with Large-scale Word Clustering
Ang Sun | Ralph Grishman | Satoshi Sekine
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

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Knowledge Base Population: Successful Approaches and Challenges
Heng Ji | Ralph Grishman
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

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Can Document Selection Help Semi-supervised Learning? A Case Study On Event Extraction
Shasha Liao | Ralph Grishman
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

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Acquiring Topic Features to improve Event Extraction: in Pre-selected and Balanced Collections
Shasha Liao | Ralph Grishman
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011

2010

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Utility Evaluation of Cross-document Information Extraction
Heng Ji | Zheng Chen | Jonathan Feldman | Antonio Gonzalez | Ralph Grishman | Vivek Upadhyay
Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics

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Large Corpus-based Semantic Feature Extraction for Pronoun Coreference
Shasha Liao | Ralph Grishman
Proceedings of the Second Workshop on NLP Challenges in the Information Explosion Era (NLPIX 2010)

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Using Document Level Cross-Event Inference to Improve Event Extraction
Shasha Liao | Ralph Grishman
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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The Impact of Task and Corpus on Event Extraction Systems
Ralph Grishman
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

The term “event extraction” covers a wide range of information extraction tasks, and methods developed and evaluated for one task may prove quite unsuitable for another. Understanding these task differences is essential to making broad progress in event extraction. We look back at the MUC and ACE tasks in terms of one characteristic, the breadth of the scenario ― how wide a range of information is subsumed in a single extraction task. We examine how this affects strategies for collecting information and methods for semi-supervised training of new extractors. We also consider the heterogeneity of corpora ― how varied the topics of documents in a corpus are. Extraction systems may be intended in principle for general news but are typically evaluated on topic-focused corpora, and this evaluation context may affect system design. As one case study, we examine the task of identifying physical attack events in news corpora, observing the effect on system performance of shifting from an attack-event-rich corpus to a more varied corpus and considering how the impact of this shift may be mitigated.

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Filtered Ranking for Bootstrapping in Event Extraction
Shasha Liao | Ralph Grishman
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)

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Semi-supervised Semantic Pattern Discovery with Guidance from Unsupervised Pattern Clusters
Ang Sun | Ralph Grishman
Coling 2010: Posters

2009

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Who, What, When, Where, Why? Comparing Multiple Approaches to the Cross-Lingual 5W Task
Kristen Parton | Kathleen R. McKeown | Bob Coyne | Mona T. Diab | Ralph Grishman | Dilek Hakkani-Tür | Mary Harper | Heng Ji | Wei Yun Ma | Adam Meyers | Sara Stolbach | Ang Sun | Gokhan Tur | Wei Xu | Sibel Yaman
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP

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Updating a Name Tagger Using Contemporary Unlabeled Data
Cristina Mota | Ralph Grishman
Proceedings of the ACL-IJCNLP 2009 Conference Short Papers

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A Parse-and-Trim Approach with Information Significance for Chinese Sentence Compression
Wei Xu | Ralph Grishman
Proceedings of the 2009 Workshop on Language Generation and Summarisation (UCNLG+Sum 2009)

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Cross-document Event Extraction and Tracking: Task, Evaluation, Techniques and Challenges
Heng Ji | Ralph Grishman | Zheng Chen | Prashant Gupta
Proceedings of the International Conference RANLP-2009

2008

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Is this NE tagger getting old?
Cristina Mota | Ralph Grishman
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

This paper focuses on the influence of changing the text time frame on the performance of a named entity tagger. We followed a twofold approach to investigate this subject: on the one hand, we analyzed a corpus that spans 8 years, and, on the other hand, we assessed the performance of a name tagger trained and tested on that corpus. We created 8 samples from the corpus, each drawn from the articles for a particular year. In terms of corpus analysis, we calculated the corpus similarity and names shared between samples. To see the effect on tagger performance, we implemented a semi-supervised name tagger based on co-training; then, we trained and tested our tagger on those samples. We observed that corpus similarity, names shared between samples, and tagger performance all decay as the time gap between the samples increases. Furthermore, we observed that the corpus similarity and names shared correlate with the tagger F-measure. These results show that named entity recognition systems may become obsolete in a short period of time.

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Refining Event Extraction through Cross-Document Inference
Heng Ji | Ralph Grishman
Proceedings of ACL-08: HLT

2007

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Question Answering Using Integrated Information Retrieval and Information Extraction
Barry Schiffman | Kathleen McKeown | Ralph Grishman | James Allan
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference

2006

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Analysis and Repair of Name Tagger Errors
Heng Ji | Ralph Grishman
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions

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Data Selection in Semi-supervised Learning for Name Tagging
Heng Ji | Ralph Grishman
Proceedings of the Workshop on Information Extraction Beyond The Document

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Re-Ranking Algorithms for Name Tagging
Heng Ji | Cynthia Rudin | Ralph Grishman
Proceedings of the Workshop on Computationally Hard Problems and Joint Inference in Speech and Language Processing

2005

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Using Semantic Relations to Refine Coreference Decisions
Heng Ji | David Westbrook | Ralph Grishman
Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing

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Improving Name Tagging by Reference Resolution and Relation Detection
Heng Ji | Ralph Grishman
Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05)

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Extracting Relations with Integrated Information Using Kernel Methods
Shubin Zhao | Ralph Grishman
Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05)

2004

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Applying Coreference to Improve Name Recognition
Heng Ji | Ralph Grishman
Proceedings of the Conference on Reference Resolution and Its Applications

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The NomBank Project: An Interim Report
Adam Meyers | Ruth Reeves | Catherine Macleod | Rachel Szekely | Veronika Zielinska | Brian Young | Ralph Grishman
Proceedings of the Workshop Frontiers in Corpus Annotation at HLT-NAACL 2004

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Discovering Relations among Named Entities from Large Corpora
Takaaki Hasegawa | Satoshi Sekine | Ralph Grishman
Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)

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Annotating Noun Argument Structure for NomBank
Adam Meyers | Ruth Reeves | Catherine Macleod | Rachel Szekely | Veronika Zielinska | Brian Young | Ralph Grishman
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Discriminative Slot Detection Using Kernel Methods
Shubin Zhao | Adam Meyers | Ralph Grishman
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

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Cross-lingual Information Extraction System Evaluation
Kiyoshi Sudo | Satoshi Sekine | Ralph Grishman
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

2003

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pre-CODIE–Crosslingual On-Demand Information Extraction
Kiyoshi Sudo | Satoshi Sekine | Ralph Grishman
Companion Volume of the Proceedings of HLT-NAACL 2003 - Demonstrations

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An Improved Extraction Pattern Representation Model for Automatic IE Pattern Acquisition
Kiyoshi Sudo | Satoshi Sekine | Ralph Grishman
Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics

2002

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Formal Mechanisms for Capturing Regularizations
Adam Meyers | Ralph Grishman | Michiko Kosaka
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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Summarization System Integrated with Named Entity Tagging and IE pattern Discovery
Chikashi Nobata | Satoshi Sekine | Hitoshi Isahara | Ralph Grishman
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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Standards & best practice for multilingual computational lexicons: ISLE MILE and more”
Nicoletta Calzolari | Ralph Grishman | Martha Palmer
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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From Resources to Applications. Designing the Multilingual ISLE Lexical Entry
Sue Atkins | Nuria Bel | Francesca Bertagna | Pierrette Bouillon | Nicoletta Calzolari | Christiane Fellbaum | Ralph Grishman | Alessandro Lenci | Catherine MacLeod | Martha Palmer | Gregor Thurmair | Marta Villegas | Antonio Zampolli
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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Towards Best Practice for Multiword Expressions in Computational Lexicons
Nicoletta Calzolari | Charles J. Fillmore | Ralph Grishman | Nancy Ide | Alessandro Lenci | Catherine MacLeod | Antonio Zampolli
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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Diversity of Scenarios in Information extraction
Silja Huttunen | Roman Yangarber | Ralph Grishman
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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Unsupervised Learning of Generalized Names
Roman Yangarber | Winston Lin | Ralph Grishman
COLING 2002: The 19th International Conference on Computational Linguistics

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Complexity of Event Structure in IE Scenarios
Silja Huttunen | Roman Yangarber | Ralph Grishman
COLING 2002: The 19th International Conference on Computational Linguistics

2001

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Covering Treebanks with GLARF
A. Meyers | Ralph Grishman | Michiko Kosaka | Shubin Zhao
Proceedings of the ACL 2001 Workshop on Sharing Tools and Resources

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Automatic Pattern Acquisition for Japanese Information Extraction
Kiyoshi Sudo | Satoshi Sekine | Ralph Grishman
Proceedings of the First International Conference on Human Language Technology Research

2000

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A Treebank of Spanish and its Application to Parsing
Antonio Moreno | Ralph Grishman | Susana López | Fernando Sánchez | Satoshi Sekine
Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00)

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The American National Corpus: A Standardized Resource for American English
Catherine Macleod | Nancy Ide | Ralph Grishman
Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00)

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Chart-Based Transfer Rule Application in Machine Translation
Adam Meyers | Michiko Kosaka | Ralph Grishman
COLING 2000 Volume 1: The 18th International Conference on Computational Linguistics

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Automatic Acquisition of Domain Knowledge for Information Extraction
Roman Yangarber | Ralph Grishman | Pasi Tapanainen | Silja Huttunen
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

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Unsupervised Discovery of Scenario-Level Patterns for Information Extraction
Roman Yangarber | Ralph Grishman | Pasi Tapanainen
Sixth Applied Natural Language Processing Conference

1998

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Deriving Transfer Rules from Dominance-Preserving Alignments
Adam Meyers | Roman Yangarber | Ralph Grishman | Catherine Macleod | Antonio Moreno-Sandoval
COLING 1998 Volume 2: The 17th International Conference on Computational Linguistics

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NYU: Description of the Proteus/PET System as Used for MUC-7 ST
Roman Yangarber | Ralph Grishman
Seventh Message Understanding Conference (MUC-7): Proceedings of a Conference Held in Fairfax, Virginia, April 29 - May 1, 1998

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NYU: Description of the MENE Named Entity System as Used in MUC-7
Andrew Borthwick | John Sterling | Eugene Agichtein | Ralph Grishman
Seventh Message Understanding Conference (MUC-7): Proceedings of a Conference Held in Fairfax, Virginia, April 29 - May 1, 1998

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Deriving Transfer Rules from Dominance-Preserving Alignments
Adam Meyers | Roman Yangarber | Ralph Grishman | Catherine Macleod | Antonio Moreno-Sandoval
36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, Volume 2

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Using NOMLEX to Produce Nominalization Patterns for Information Extraction
Adam Meyers | Catherine Macleod | Roman Yangarber | Ralph Grishman | Leslie Barrett | Ruth Reeves
The Computational Treatment of Nominals

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Exploiting Diverse Knowledge Sources via Maximum Entropy in Named Entity Recognition
Andrew Borthwick | John Sterling | Eugene Agichtein | Ralph Grishman
Sixth Workshop on Very Large Corpora

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A Decision Tree Method for Finding and Classifying Names in Japanese Texts
Satoshi Sekine | Ralph Grishman | Hiroyuki Shinnou
Sixth Workshop on Very Large Corpora

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A multilingual procedure for dictionary-based sentence alignment
Adam Meyers | Michiko Kosaka | Ralph Grishman
Proceedings of the Third Conference of the Association for Machine Translation in the Americas: Technical Papers

This paper describes a sentence alignment technique based on a machine readable dictionary. Alignment takes place in a single pass through the text, based on the scores of matches between pairs of source and target sentences. Pairings consisting of sets of matches are evaluated using a version of the Gale-Shapely solution to the stable marriage problem. An algorithm is described which can handle N-to-1 (or 1-to-N) matches, for n ≥ 0, i.e., deletions, 1-to-1 (including scrambling), and 1-to-many matches. A simple frequency based method for acquiring supplemental dictionary entries is also discussed. We achieve high quality alignments using available bilingual dictionaries, both for closely related language pairs (Spanish/English) and more distantly related pairs (Japanese/English).

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Research in Information Extraction: 1996-98
Ralph Grishman
TIPSTER TEXT PROGRAM PHASE III: Proceedings of a Workshop held at Baltimore, Maryland, October 13-15, 1998

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Transforming Examples into Patterns for Information Extraction
Roman Yangarber | Ralph Grishman
TIPSTER TEXT PROGRAM PHASE III: Proceedings of a Workshop held at Baltimore, Maryland, October 13-15, 1998

1996

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The Role of Syntax in Information Extraction
Ralph Grishman
TIPSTER TEXT PROGRAM PHASE II: Proceedings of a Workshop held at Vienna, Virginia, May 6-8, 1996

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Building an Architecture: A CAWG Saga
Ralph Grishman
TIPSTER TEXT PROGRAM PHASE II: Proceedings of a Workshop held at Vienna, Virginia, May 6-8, 1996

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TIPSTER Text Phase II Architecture Design Version 2.1p 19 June 1996
Ralph Grishman
TIPSTER TEXT PROGRAM PHASE II: Proceedings of a Workshop held at Vienna, Virginia, May 6-8, 1996

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Design of the MUC-6 Evaluation
Ralph Grishman | Beth Sundheim
TIPSTER TEXT PROGRAM PHASE II: Proceedings of a Workshop held at Vienna, Virginia, May 6-8, 1996

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Alignment of Shared Forests for Bilingual Corpora
Adam Meyers | Roman Yangarber | Ralph Grishman
COLING 1996 Volume 1: The 16th International Conference on Computational Linguistics

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Message Understanding Conference- 6: A Brief History
Ralph Grishman | Beth Sundheim
COLING 1996 Volume 1: The 16th International Conference on Computational Linguistics

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The Influence of Tagging on the Classification of Lexical Complements
Catherine Macleod | Adam Meyers | Ralph Grishman
COLING 1996 Volume 1: The 16th International Conference on Computational Linguistics

1995

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A Corpus-based Probabilistic Grammar with Only Two Non-terminals
Satoshi Sekine | Ralph Grishman
Proceedings of the Fourth International Workshop on Parsing Technologies

The availability of large, syntactically-bracketed corpora such as the Penn Tree Bank affords us the opportunity to automatically build or train broad-coverage grammars, and in particular to train probabilistic grammars. A number of recent parsing experiments have also indicated that grammars whose production probabilities are dependent on the context can be more effective than context-free grammars in selecting a correct parse. To make maximal use of context, we have automatically constructed, from the Penn Tree Bank version 2, a grammar in which the symbols S and NP are the only real nonterminals, and the other non-terminals or grammatical nodes are in effect embedded into the right-hand-sides of the S and NP rules. For example, one of the rules extracted from the tree bank would be S -> NP VBX JJ CC VBX NP [1] ( where NP is a non-terminal and the other symbols are terminals – part-of-speech tags of the Tree Bank). The most common structure in the Tree Bank associated with this expansion is (S NP (VP (VP VBX (ADJ JJ) CC (VP VBX NP)))) [2]. So if our parser uses rule [1] in parsing a sentence, it will generate structure [2] for the corresponding part of the sentence. Using 94% of the Penn Tree Bank for training, we extracted 32,296 distinct rules ( 23,386 for S, and 8,910 for NP). We also built a smaller version of the grammar based on higher frequency patterns for use as a back-up when the larger grammar is unable to produce a parse due to memory limitation. We applied this parser to 1,989 Wall Street Journal sentences (separate from the training set and with no limit on sentence length). Of the parsed sentences (1,899), the percentage of no-crossing sentences is 33.9%, and Parseval recall and precision are 73.43% and 72 .61%.

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Design of the MUC-6 Evaluation
Ralph Grishman | Beth Sundheim
Sixth Message Understanding Conference (MUC-6): Proceedings of a Conference Held in Columbia, Maryland, November 6-8, 1995

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The NYU System for MUC-6 or Where’s the Syntax?
Ralph Grishman
Sixth Message Understanding Conference (MUC-6): Proceedings of a Conference Held in Columbia, Maryland, November 6-8, 1995

1994

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Comlex Syntax: Building a Computational Lexicon
Ralph Grishman | Catherine Macleod | Adam Meyers
COLING 1994 Volume 1: The 15th International Conference on Computational Linguistics

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Generalizing Automatically Generated Selectional Patterns
Ralph Grishman | John Sterling
COLING 1994 Volume 2: The 15th International Conference on Computational Linguistics

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The Comlex Syntax Project: The First Year
Catherine Macleod | Ralph Grishman | Adam Meyers
Human Language Technology: Proceedings of a Workshop held at Plainsboro, New Jersey, March 8-11, 1994

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Whither Written Language Evaluation?
Ralph Grishman
Human Language Technology: Proceedings of a Workshop held at Plainsboro, New Jersey, March 8-11, 1994

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Research in Natural Language Processing
Ralph Grishman
Human Language Technology: Proceedings of a Workshop held at Plainsboro, New Jersey, March 8-11, 1994

1993

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Smoothing of Automatically Generated Selectional Constraints
Ralph Grishman | John Sterling
Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993

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Session 10: THE LEXICON
Ralph Grishman
Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993

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The COMLEX Syntax Project
Ralph Grishman | Catherine Macleod | Susanne Wolff
Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993

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Research in Natural Language Processing
Ralph Grishman
Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993

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New York University Description of the PROTEUS System as Used for MUC-5
Ralph Grishman | John Sterling
Fifth Message Understanding Conference (MUC-5): Proceedings of a Conference Held in Baltimore, Maryland, August 25-27, 1993

1992

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New York University PROTEUS System: MUC-4 Test Results and Analysis
Ralph Grishman | John Sterling | Catherine Macleod
Fourth Message Uunderstanding Conference (MUC-4): Proceedings of a Conference Held in McLean, Virginia, June 16-18, 1992

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New York University Description of the PROTEUS System as Used for MUC-4
Ralph Grishman | Catherine Macleod | John Sterling
Fourth Message Uunderstanding Conference (MUC-4): Proceedings of a Conference Held in McLean, Virginia, June 16-18, 1992

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Research in Natural Language Processing
Ralph Grishman
Speech and Natural Language: Proceedings of a Workshop Held at Harriman, New York, February 23-26, 1992

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Acquisition of Selectional Patterns
Ralph Grishman | John Sterling
COLING 1992 Volume 2: The 14th International Conference on Computational Linguistics

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Combining rationalist and empiricist approaches to machine translation
Ralph Grishman | Michiko Kosaka
Proceedings of the Fourth Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages

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Evaluating Parsing Strategies Using Standardized Parse Files
Ralph Grishman | Catherine Macleod | John Sterling
Third Conference on Applied Natural Language Processing

1991

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New York University PROTEUS System: MUC-3 Test Results and Analysis
Ralph Grishman | John Sterling | Catherine Macleod
Third Message Uunderstanding Conference (MUC-3): Proceedings of a Conference Held in San Diego, California, May 21-23, 1991

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New York University: Description of the PROTEUS System as Used for MUC-3
Ralph Grishman | John Sterling | Catherine Macleod
Third Message Uunderstanding Conference (MUC-3): Proceedings of a Conference Held in San Diego, California, May 21-23, 1991

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Computational Aspects of Discourse in the Context of MUC-3
Lucja Iwanska | Douglas Appelt | Damaris Ayuso | Kathy Dahlgren | Bonnie Glover Stalls | Ralph Grishman | George Krupka | Christine Montgomery | Ellen Riloff
Third Message Uunderstanding Conference (MUC-3): Proceedings of a Conference Held in San Diego, California, May 21-23, 1991

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A Procedure for Quantitatively Comparing the Syntactic Coverage of English Grammars
E. Black | S. Abney | D. Flickenger | C. Gdaniec | R. Grishman | P. Harrison | D. Hindle | R. Ingria | F. Jelinek | J. Klavans | M. Liberman | M. Marcus | S. Roukos | B. Santorini | T. Strzalkowski
Speech and Natural Language: Proceedings of a Workshop Held at Pacific Grove, California, February 19-22, 1991

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Robust and Portable Text Processing
Ralph Grishman
Speech and Natural Language: Proceedings of a Workshop Held at Pacific Grove, California, February 19-22, 1991

1990

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Causal and Temporal Text Analysis: The Role of the Domain Model
Ralph Grishman | Tomasz Ksiezyk
COLING 1990 Volume 3: Papers presented to the 13th International Conference on Computational Linguistics

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Information Extraction and Semantic Constraints
Ralph Grishman | John Sterling
COLING 1990 Volume 3: Papers presented to the 13th International Conference on Computational Linguistics

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Statistical Parsing of Messages
Mahesh V. Chitrao | Ralph Grishman
Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, June 24-27,1990

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Research in Text Processing: Creating Robust and Portable Systems
Ralph Grishman
Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, June 24-27,1990

1989

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Natural Language Understanding
Ralph Grishman
Speech and Natural Language: Proceedings of a Workshop Held at Philadelphia, Pennsylvania, February 21-23, 1989

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Analyzing Telegraphic Messages
Ralph Grishman | John Sterling
Speech and Natural Language: Proceedings of a Workshop Held at Philadelphia, Pennsylvania, February 21-23, 1989

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Preference Semantics for Message Understanding
Ralph Grishman | John Sterling
Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989

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Data Collection and Evaluation II
Ralph Grishman
Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989

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Robust Natural Language Analysis
Ralph Grishman
Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989

1988

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A comparative study of Japanese and English sublanguage patterns
Virginia Teller | Michiko Kosaka | Ralph Grishman
Proceedings of the Second Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages

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Responding to Semantically Ill-Formed Input
Ralph Grishman | Ping Peng
Second Conference on Applied Natural Language Processing

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Evaluation of a Parallel Chart Parser
Ralph Grishman | Mahesh Chitrao
Second Conference on Applied Natural Language Processing

1986

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Discovery Procedures for Sublanguage Selectional Patterns: Initial Experiments
Ralph Grishman | Lynette Hirschman | Ngo Thanh Nhan
Computational Linguistics. Formerly the American Journal of Computational Linguistics, Volume 12, Number 3, July-September 1986

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PROTEUS and PUNDIT: RESEARCH IN TEXT UNDERSTANDING at the Department of Computer Science, New York University and System Development Corporation -- A Burroughs Company
Ralph Grishman | Lynette Hirschman
Strategic Computing - Natural Language Workshop: Proceedings of a Workshop Held at Marina del Rey, California, May 1-2, 1986

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Model-based Analysis of Messages about Equipment
Ralph Grishman | Tomasz Ksiezyk | Ngo Thanh Nhan
Strategic Computing - Natural Language Workshop: Proceedings of a Workshop Held at Marina del Rey, California, May 1-2, 1986

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An Equipment Model and Its Role in the Interpretation of Nominal Compounds
Tomasz Ksiezyk | Ralph Grishman
Strategic Computing - Natural Language Workshop: Proceedings of a Workshop Held at Marina del Rey, California, May 1-2, 1986

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Tutorial Abstracts
Ralph Grishman
24th Annual Meeting of the Association for Computational Linguistics

1984

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Automated Determination of Sublanguage Syntactic Usage
Ralph Grishman | Ngo Thanh Nhan | Elaine Marsh | Lynette Hirschman
10th International Conference on Computational Linguistics and 22nd Annual Meeting of the Association for Computational Linguistics

1983

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Isolating Domain Dependencies in Natural Language Interfaces
R. Grishman | L. Hirschman | C. Friedman
First Conference on Applied Natural Language Processing

1982

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Natural Language Interfaces Using Limited Semantic Information
Ralph Grishman | Lynette Hirschman | Carol Friedman
Coling 1982: Proceedings of the Ninth International Conference on Computational Linguistics

1981

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Parsing
Ralph Grishman
19th Annual Meeting of the Association for Computational Linguistics

1980

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Conjunctions and Modularity in Language Analysis Procedures
Ralph Grishman
COLING 1980 Volume 1: The 8th International Conference on Computational Linguistics

1979

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Response Generation in Question - Answering Systems
Ralph Grishman
17th Annual Meeting of the Association for Computational Linguistics

1976

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A Survey of Syntactic Analysis Procedures for Natural Language
Ralph Grishman
American Journal of Computational Linguistics (May 1976)

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