Bill MacCartney


2014

pdf bib
On the Importance of Text Analysis for Stock Price Prediction
Heeyoung Lee | Mihai Surdeanu | Bill MacCartney | Dan Jurafsky
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We investigate the importance of text analysis for stock price prediction. In particular, we introduce a system that forecasts companies’ stock price changes (UP, DOWN, STAY) in response to financial events reported in 8-K documents. Our results indicate that using text boosts prediction accuracy over 10% (relative) over a strong baseline that incorporates many financially-rooted features. This impact is most important in the short term (i.e., the next day after the financial event) but persists for up to five days.

2009

pdf bib
An extended model of natural logic
Bill MacCartney | Christopher D. Manning
Proceedings of the Eight International Conference on Computational Semantics

2008

pdf bib
A Phrase-Based Alignment Model for Natural Language Inference
Bill MacCartney | Michel Galley | Christopher D. Manning
Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing

pdf bib
Modeling Semantic Containment and Exclusion in Natural Language Inference
Bill MacCartney | Christopher D. Manning
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)

2007

pdf bib
Learning Alignments and Leveraging Natural Logic
Nathanael Chambers | Daniel Cer | Trond Grenager | David Hall | Chloe Kiddon | Bill MacCartney | Marie-Catherine de Marneffe | Daniel Ramage | Eric Yeh | Christopher D. Manning
Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing

pdf bib
Natural Logic for Textual Inference
Bill MacCartney | Christopher D. Manning
Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing

2006

pdf bib
Learning to recognize features of valid textual entailments
Bill MacCartney | Trond Grenager | Marie-Catherine de Marneffe | Daniel Cer | Christopher D. Manning
Proceedings of the Human Language Technology Conference of the NAACL, Main Conference

pdf bib
Generating Typed Dependency Parses from Phrase Structure Parses
Marie-Catherine de Marneffe | Bill MacCartney | Christopher D. Manning
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

This paper describes a system for extracting typed dependency parses of English sentences from phrase structure parses. In order to capture inherent relations occurring in corpus texts that can be critical in real-world applications, many NP relations are included in the set of grammatical relations used. We provide a comparison of our system with Minipar and the Link parser. The typed dependency extraction facility described here is integrated in the Stanford Parser, available for download.

2004

pdf bib
Solving logic puzzles: From robust processing to precise semantics
Iddo Lev | Bill MacCartney | Christopher Manning | Roger Levy
Proceedings of the 2nd Workshop on Text Meaning and Interpretation