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Learning Biological Processes with Global Constraints
Aju Thalappillil Scaria, Jonathan Berant, Mengqiu Wang, Christopher D. Manning, Justin Lewis, Brittany Harding, and Peter ClarkEMNLP • 2013 Biological processes are complex phenomena involving a series of events that are related to one another through various relationships. Systems that can understand and reason over biological processes would dramatically improve the performance of semantic…Semi-Markov Phrase-based Monolingual Alignment
Xuchen Yao, Benjamin Van Durme, Chris Callision-Burch, and Peter ClarkEMNLP • 2013 We introduce a novel discriminative model for phrase-based monolingual alignment using a semi-Markov CRF. Our model achieves stateof-the-art alignment accuracy on two phrasebased alignment datasets (RTE and paraphrase), while doing significantly better than…Probabilistic coherence, logical consistency, and Bayesian learning: Neural language models as epistemic agents
Gregor Betz, Kyle RichardsonPLoS ONE • 2013 It is argued that suitably trained neural language models exhibit key properties of epistemic agency: they hold probabilistically coherent and logically consistent degrees of belief, which they can rationally revise in the face of novel evidence. To this…Constructing a Textual KB from a Biology TextBook
Peter Clark, Phil Harrison, Niranjan Balasubramanian, and Oren EtzioniNAACL-HLT • AKBC Workshop • 2012 As part of our work on building a "knowledgeable textbook" about biology, we are developing a textual question-answering (QA) system that can answer certain classes of biology questions posed by users. In support of that, we are building a "textual KB" - an…