Research Interests

I research natural language processing (NLP) and learning about the world from text with minimal supervision. I apply modern NLP and machine learning techniques to the Web to learn how events and people interact. I am also interested in information extraction to help people better understand large amounts of text. I occasionally try to model time: when events start, how long, and in what order they occur.

Student Collaboration

I am always open to advising undergraduate research. Come talk to me if you're interested. Topics ranging from social media like Twitter to intelligent systems that read the news are ripe for study.

Education

Ph.D., Computer Science, Stanford University, 2011

M.S., Computer Science, University of Rochester, 2003

B.S., Computer Science, University of Rochester, 2002

Selected Publications (view all 60 with downloads)

Using Commonsense Knowledge to Answer Why-Questions	EMNLP 2022
TellMeWhy: A Dataset for Answering Why-Questions in Narratives	ACL 2021
Character-Based Models for Adversarial Phone Number Extraction: Preventing Human Sex Trafficking	WNUT 2019
Event Representations with Tensor-based Compositions	AAAI 2018
A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories	NAACL 2016
Identifying Political Sentiment between Nation States with Social Media	EMNLP 2015
Dense Event Ordering with a Multi-Pass Architecture	TACL 2014
Template-Based Information Extraction without the Templates	ACL 2011
A Multi-Pass Sieve for Coreference Resolution	EMNLP 2010
Unsupervised Learning of Narrative Schemas and their Participants	ACL 2009
view all 60 with downloads

Data

Adversarial Phone Extraction

Twitter DDoS Attacks

Twitter Users/Aliases

Story Cloze Test Corpora

Nation-Nation Sentiment Data and Visualization

CAEVO: Dense Event Ordering

Narrative Cloze Evaluation (Gigaword Corpus NYT labeled)

Narrative Schemas Data

Political Tweets

Document Timestamp Prediction

Pseudo-Word Evaluation Data

TimeBank Event Pairs

Event Duration Lexicon