Ellen Riloff

Also published as: E. Riloff


2021

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Exploiting Definitions for Frame Identification
Tianyu Jiang | Ellen Riloff
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Frame identification is one of the key challenges for frame-semantic parsing. The goal of this task is to determine which frame best captures the meaning of a target word or phrase in a sentence. We present a new model for frame identification that uses a pre-trained transformer model to generate representations for frames and lexical units (senses) using their formal definitions in FrameNet. Our frame identification model assesses the suitability of a frame for a target word in a sentence based on the semantic coherence of their meanings. We evaluate our model on three data sets and show that it consistently achieves better performance than previous systems.

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Learning Prototypical Functions for Physical Artifacts
Tianyu Jiang | Ellen Riloff
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Humans create things for a reason. Ancient people created spears for hunting, knives for cutting meat, pots for preparing food, etc. The prototypical function of a physical artifact is a kind of commonsense knowledge that we rely on to understand natural language. For example, if someone says “She borrowed the book” then you would assume that she intends to read the book, or if someone asks “Can I use your knife?” then you would assume that they need to cut something. In this paper, we introduce a new NLP task of learning the prototypical uses for human-made physical objects. We use frames from FrameNet to represent a set of common functions for objects, and describe a manually annotated data set of physical objects labeled with their prototypical function. We also present experimental results for this task, including BERT-based models that use predictions from masked patterns as well as artifact sense definitions from WordNet and frame definitions from FrameNet.

2020

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Recognizing Euphemisms and Dysphemisms Using Sentiment Analysis
Christian Felt | Ellen Riloff
Proceedings of the Second Workshop on Figurative Language Processing

This paper presents the first research aimed at recognizing euphemistic and dysphemistic phrases with natural language processing. Euphemisms soften references to topics that are sensitive, disagreeable, or taboo. Conversely, dysphemisms refer to sensitive topics in a harsh or rude way. For example, “passed away” and “departed” are euphemisms for death, while “croaked” and “six feet under” are dysphemisms for death. Our work explores the use of sentiment analysis to recognize euphemistic and dysphemistic language. First, we identify near-synonym phrases for three topics (firing, lying, and stealing) using a bootstrapping algorithm for semantic lexicon induction. Next, we classify phrases as euphemistic, dysphemistic, or neutral using lexical sentiment cues and contextual sentiment analysis. We introduce a new gold standard data set and present our experimental results for this task.

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Exploring the Role of Context to Distinguish Rhetorical and Information-Seeking Questions
Yuan Zhuang | Ellen Riloff
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop

Social media posts often contain questions, but many of the questions are rhetorical and do not seek information. Our work studies the problem of distinguishing rhetorical and information-seeking questions on Twitter. Most work has focused on features of the question itself, but we hypothesize that the prior context plays a role too. This paper introduces a new dataset containing questions in tweets paired with their prior tweets to provide context. We create classification models to assess the difficulty of distinguishing rhetorical and information-seeking questions, and experiment with different properties of the prior context. Our results show that the prior tweet and topic features can improve performance on this task.

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Affective Event Classification with Discourse-enhanced Self-training
Yuan Zhuang | Tianyu Jiang | Ellen Riloff
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Prior research has recognized the need to associate affective polarities with events and has produced several techniques and lexical resources for identifying affective events. Our research introduces new classification models to assign affective polarity to event phrases. First, we present a BERT-based model for affective event classification and show that the classifier achieves substantially better performance than a large affective event knowledge base. Second, we present a discourse-enhanced self-training method that iteratively improves the classifier with unlabeled data. The key idea is to exploit event phrases that occur with a coreferent sentiment expression. The discourse-enhanced self-training algorithm iteratively labels new event phrases based on both the classifier’s predictions and the polarities of the event’s coreferent sentiment expressions. Our results show that discourse-enhanced self-training further improves both recall and precision for affective event classification.

2019

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Improving Human Needs Categorization of Events with Semantic Classification
Haibo Ding | Ellen Riloff | Zhe Feng
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)

Human Needs categories have been used to characterize the reason why an affective event is positive or negative. For example, “I got the flu” and “I got fired” are both negative (undesirable) events, but getting the flu is a Health problem while getting fired is a Financial problem. Previous work created learning models to assign events to Human Needs categories based on their words and contexts. In this paper, we introduce an intermediate step that assigns words to relevant semantic concepts. We create lightly supervised models that learn to label words with respect to 10 semantic concepts associated with Human Needs categories, and incorporate these labels as features for event categorization. Our results show that recognizing relevant semantic concepts improves both the recall and precision of Human Needs categorization for events.

2018

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Human Needs Categorization of Affective Events Using Labeled and Unlabeled Data
Haibo Ding | Ellen Riloff
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

We often talk about events that impact us positively or negatively. For example “I got a job” is good news, but “I lost my job” is bad news. When we discuss an event, we not only understand its affective polarity but also the reason why the event is beneficial or detrimental. For example, getting or losing a job has affective polarity primarily because it impacts us financially. Our work aims to categorize affective events based upon human need categories that often explain people’s motivations and desires: PHYSIOLOGICAL, HEALTH, LEISURE, SOCIAL, FINANCIAL, COGNITION, and FREEDOM. We create classification models based on event expressions as well as models that use contexts surrounding event mentions. We also design a co-training model that learns from unlabeled data by simultaneously training event expression and event context classifiers in an iterative learning process. Our results show that co-training performs well, producing substantially better results than the individual classifiers.

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Learning Prototypical Goal Activities for Locations
Tianyu Jiang | Ellen Riloff
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

People go to different places to engage in activities that reflect their goals. For example, people go to restaurants to eat, libraries to study, and churches to pray. We refer to an activity that represents a common reason why people typically go to a location as a prototypical goal activity (goal-act). Our research aims to learn goal-acts for specific locations using a text corpus and semi-supervised learning. First, we extract activities and locations that co-occur in goal-oriented syntactic patterns. Next, we create an activity profile matrix and apply a semi-supervised label propagation algorithm to iteratively revise the activity strengths for different locations using a small set of labeled data. We show that this approach outperforms several baseline methods when judged against goal-acts identified by human annotators.

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Identifying Affective Events and the Reasons for their Polarity
Ellen Riloff
Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis

Many events have a positive or negative impact on our lives (e.g., “I bought a house” is typically good news, but ”My house burned down” is bad news). Recognizing events that have affective polarity is essential for narrative text understanding, conversational dialogue, and applications such as summarization and sarcasm detection. We will discuss our recent work on identifying affective events and categorizing them based on the underlying reasons for their affective polarity. First, we will describe a weakly supervised learning method to induce a large set of affective events from a text corpus by optimizing for semantic consistency. Second, we will present models to classify affective events based on Human Need Categories, which often explain people’s motivations and desires. Our best results use a co-training model that consists of event expression and event context classifiers and exploits both labeled and unlabeled texts. We will conclude with a discussion of interesting directions for future work in this area.

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Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Ellen Riloff | David Chiang | Julia Hockenmaier | Jun’ichi Tsujii
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

2017

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Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog
Shereen Oraby | Vrindavan Harrison | Amita Misra | Ellen Riloff | Marilyn Walker
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

Effective models of social dialog must understand a broad range of rhetorical and figurative devices. Rhetorical questions (RQs) are a type of figurative language whose aim is to achieve a pragmatic goal, such as structuring an argument, being persuasive, emphasizing a point, or being ironic. While there are computational models for other forms of figurative language, rhetorical questions have received little attention to date. We expand a small dataset from previous work, presenting a corpus of 10,270 RQs from debate forums and Twitter that represent different discourse functions. We show that we can clearly distinguish between RQs and sincere questions (0.76 F1). We then show that RQs can be used both sarcastically and non-sarcastically, observing that non-sarcastic (other) uses of RQs are frequently argumentative in forums, and persuasive in tweets. We present experiments to distinguish between these uses of RQs using SVM and LSTM models that represent linguistic features and post-level context, achieving results as high as 0.76 F1 for “sarcastic” and 0.77 F1 for “other” in forums, and 0.83 F1 for both “sarcastic” and “other” in tweets. We supplement our quantitative experiments with an in-depth characterization of the linguistic variation in RQs.

2016

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Distinguishing Past, On-going, and Future Events: The EventStatus Corpus
Ruihong Huang | Ignacio Cases | Dan Jurafsky | Cleo Condoravdi | Ellen Riloff
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

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Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue
Shereen Oraby | Vrindavan Harrison | Lena Reed | Ernesto Hernandez | Ellen Riloff | Marilyn Walker
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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Automatically Inferring Implicit Properties in Similes
Ashequl Qadir | Ellen Riloff | Marilyn A. Walker
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2015

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Learning to Recognize Affective Polarity in Similes
Ashequl Qadir | Ellen Riloff | Marilyn Walker
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

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And That’s A Fact: Distinguishing Factual and Emotional Argumentation in Online Dialogue
Shereen Oraby | Lena Reed | Ryan Compton | Ellen Riloff | Marilyn Walker | Steve Whittaker
Proceedings of the 2nd Workshop on Argumentation Mining

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Stacked Generalization for Medical Concept Extraction from Clinical Notes
Youngjun Kim | Ellen Riloff
Proceedings of BioNLP 15

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Extracting Information about Medication Use from Veterinary Discussions
Haibo Ding | Ellen Riloff
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2014

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User Type Classification of Tweets with Implications for Event Recognition
Lalindra De Silva | Ellen Riloff
Proceedings of the Joint Workshop on Social Dynamics and Personal Attributes in Social Media

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Learning Emotion Indicators from Tweets: Hashtags, Hashtag Patterns, and Phrases
Ashequl Qadir | Ellen Riloff
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

2013

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Sarcasm as Contrast between a Positive Sentiment and Negative Situation
Ellen Riloff | Ashequl Qadir | Prafulla Surve | Lalindra De Silva | Nathan Gilbert | Ruihong Huang
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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Classifying Message Board Posts with an Extracted Lexicon of Patient Attributes
Ruihong Huang | Ellen Riloff
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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Multi-faceted Event Recognition with Bootstrapped Dictionaries
Ruihong Huang | Ellen Riloff
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Bootstrapped Learning of Emotion Hashtags #hashtags4you
Ashequl Qadir | Ellen Riloff
Proceedings of the 4th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis

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Domain-Specific Coreference Resolution with Lexicalized Features
Nathan Gilbert | Ellen Riloff
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2012

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Ensemble-based Semantic Lexicon Induction for Semantic Tagging
Ashequl Qadir | Ellen Riloff
*SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012)

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Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Eric Fosler-Lussier | Ellen Riloff | Srinivas Bangalore
Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Bootstrapped Training of Event Extraction Classifiers
Ruihong Huang | Ellen Riloff
Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics

2011

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The Role of Information Extraction in the Design of a Document Triage Application for Biocuration
Sandeep Pokkunuri | Cartic Ramakrishnan | Ellen Riloff | Eduard Hovy | Gully Burns
Proceedings of BioNLP 2011 Workshop

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The Taming of Reconcile as a Biomedical Coreference Resolver
Youngjun Kim | Ellen Riloff | Nathan Gilbert
Proceedings of BioNLP Shared Task 2011 Workshop

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Classifying Sentences as Speech Acts in Message Board Posts
Ashequl Qadir | Ellen Riloff
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

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Peeling Back the Layers: Detecting Event Role Fillers in Secondary Contexts
Ruihong Huang | Ellen Riloff
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

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Improving Classification of Medical Assertions in Clinical Notes
Youngjun Kim | Ellen Riloff | Stéphane Meystre
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

2010

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Toward Plot Units: Automatic Affect State Analysis
Amit Goyal | Ellen Riloff | Hal Daume III | Nathan Gilbert
Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text

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Inducing Domain-Specific Semantic Class Taggers from (Almost) Nothing
Ruihong Huang | Ellen Riloff
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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Coreference Resolution with Reconcile
Veselin Stoyanov | Claire Cardie | Nathan Gilbert | Ellen Riloff | David Buttler | David Hysom
Proceedings of the ACL 2010 Conference Short Papers

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Automatically Producing Plot Unit Representations for Narrative Text
Amit Goyal | Ellen Riloff | Hal Daumé III
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing

2009

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Conundrums in Noun Phrase Coreference Resolution: Making Sense of the State-of-the-Art
Veselin Stoyanov | Nathan Gilbert | Claire Cardie | Ellen Riloff
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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A Unified Model of Phrasal and Sentential Evidence for Information Extraction
Siddharth Patwardhan | Ellen Riloff
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

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Toward Completeness in Concept Extraction and Classification
Eduard Hovy | Zornitsa Kozareva | Ellen Riloff
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

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Corpus-based Semantic Lexicon Induction with Web-based Corroboration
Sean Igo | Ellen Riloff
Proceedings of the Workshop on Unsupervised and Minimally Supervised Learning of Lexical Semantics

2008

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Semantic Class Learning from the Web with Hyponym Pattern Linkage Graphs
Zornitsa Kozareva | Ellen Riloff | Eduard Hovy
Proceedings of ACL-08: HLT

2007

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Effective Information Extraction with Semantic Affinity Patterns and Relevant Regions
Siddharth Patwardhan | Ellen Riloff
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

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Proceedings of the ACL 2007 Student Research Workshop
Chris Biemann | Violeta Seretan | Ellen Riloff
Proceedings of the ACL 2007 Student Research Workshop

2006

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Learning Domain-Specific Information Extraction Patterns from the Web
Siddharth Patwardhan | Ellen Riloff
Proceedings of the Workshop on Information Extraction Beyond The Document

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Feature Subsumption for Opinion Analysis
Ellen Riloff | Siddharth Patwardhan | Janyce Wiebe
Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing

2005

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Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns
Yejin Choi | Claire Cardie | Ellen Riloff | Siddharth Patwardhan
Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing

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OpinionFinder: A System for Subjectivity Analysis
Theresa Wilson | Paul Hoffmann | Swapna Somasundaran | Jason Kessler | Janyce Wiebe | Yejin Choi | Claire Cardie | Ellen Riloff | Siddharth Patwardhan
Proceedings of HLT/EMNLP 2005 Interactive Demonstrations

2004

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Unsupervised Learning of Contextual Role Knowledge for Coreference Resolution
David Bean | Ellen Riloff
Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004

2003

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Learning subjective nouns using extraction pattern bootstrapping
Ellen Riloff | Janyce Wiebe | Theresa Wilson
Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003

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Learning Extraction Patterns for Subjective Expressions
Ellen Riloff | Janyce Wiebe
Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing

2002

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Exploiting Strong Syntactic Heuristics and Co-Training to Learn Semantic Lexicons
William Phillips | Ellen Riloff
Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP 2002)

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A Bootstrapping Method for Learning Semantic Lexicons using Extraction Pattern Contexts
Michael Thelen | Ellen Riloff
Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP 2002)

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Inducing Information Extraction Systems for New Languages via Cross-language Projection
Ellen Riloff | Charles Schafer | David Yarowsky
COLING 2002: The 19th International Conference on Computational Linguistics

2001

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Looking Under the Hood: Tools for Diagnosing Your Question Answering Engine
Eric Breck | Marc Light | Gideon Mann | Ellen Riloff | Brianne Brown | Pranav Anand
Proceedings of the ACL 2001 Workshop on Open-Domain Question Answering

2000

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A Rule-based Question Answering System for Reading Comprehension Tests
Ellen Riloff | Michael Thelen
ANLP-NAACL 2000 Workshop: Reading Comprehension Tests as Evaluation for Computer-Based Language Understanding Systems

1999

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Corpus-Based Identification of Non-Anaphoric Noun Phrases
David L. Bean | Ellen Riloff
Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics

1998

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An Empirical Approach to Conceptual Case Frame Acquisition
Ellen Riloff | Mark Schmelzenbach
Sixth Workshop on Very Large Corpora

1997

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A Corpus-Based Approach for Building Semantic Lexicons
Ellen Riloff | Jessica Shepherd
Second Conference on Empirical Methods in Natural Language Processing

1995

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Automatically Acquiring Conceptual Patterns without an Annotated Corpus
Ellen Riloff | Jay Shoen
Third Workshop on Very Large Corpora

1993

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UMass/Hughes: Description of the CIRCUS System Used for TIPSTER Text
W. Lehnert | J. McCarthy | S. Soderland | E. Riloff | C. Cardie | J. Peterson | F. Feng
TIPSTER TEXT PROGRAM: PHASE I: Proceedings of a Workshop held at Fredricksburg, Virginia, September 19-23, 1993

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Dictionary Construction by Domain Experts
Ellen Riloff | Wendy G. Lehnert
TIPSTER TEXT PROGRAM: PHASE I: Proceedings of a Workshop held at Fredricksburg, Virginia, September 19-23, 1993

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UMass/Hughes: Description of the CIRCUS System Used for MUC-51
W. Lehnert | J. McCarthy | S. Soderland | E. Riloff | C. Cardie | J. Peterson | F. Feng
Fifth Message Understanding Conference (MUC-5): Proceedings of a Conference Held in Baltimore, Maryland, August 25-27, 1993

1992

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University of Massachusetts: MUC-4 Test Results and Analysis
W. Lehnert | C. Cardie | D. Fisher | J. McCarthy | E. Riloff | S. Soderland
Fourth Message Uunderstanding Conference (MUC-4): Proceedings of a Conference Held in McLean, Virginia, June 16-18, 1992

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University of Massachusetts: Description of the CIRCUS System as Used for MUC-4
W. Lehnert | C. Cardie | D. Fisher | J. McCarthy | E. Riloff | S. Soderland
Fourth Message Uunderstanding Conference (MUC-4): Proceedings of a Conference Held in McLean, Virginia, June 16-18, 1992

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Classifying Texts Using Relevancy Signatures
Ellen Riloff | Wendy Lehnert
Speech and Natural Language: Proceedings of a Workshop Held at Harriman, New York, February 23-26, 1992

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Augmenting With Slot Filler Relevancy Signatures Data
Ellen Riloff | Wendy Lehnert
Speech and Natural Language: Proceedings of a Workshop Held at Harriman, New York, February 23-26, 1992

1991

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University of Massachusetts: MUC-3 Test Results and Analysis
Wendy Lehnert | Claire Cardie | David Fisher | Ellen Riloff | Robert Williams
Third Message Uunderstanding Conference (MUC-3): Proceedings of a Conference Held in San Diego, California, May 21-23, 1991

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University of Massachusetts: Description of the CIRCUS System as Used for MUC-3
Wendy Lehnert | Claire Cardie | David Fisher | Ellen Riloff | Robert Williams
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