Papers

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Viewing 801-810 of 813 papers
  • Modeling Biological Processes for Reading Comprehension

    Jonathan Berant, Vivek Srikumar, Pei-Chun Chen, Brad Huang, Christopher D. Manning, Abby Vander Linden, Brittany Harding, and Peter ClarkEMNLP2014 Machine reading calls for programs that read and understand text, but most current work only attempts to extract facts from redundant web-scale corpora. In this paper, we focus on a new reading comprehension task that requires complex reasoning over a single…
  • Open Question Answering Over Curated and Extracted Knowledge Bases

    Anthony Fader, Luke Zettlemoyer, and Oren EtzioniKDD2014 We consider the problem of open-domain question answering (Open QA) over massive knowledge bases (KBs). Existing approaches use either manually curated KBs like Freebase or KBs automatically extracted from unstructured text. In this paper, we present oqa, the…
  • Diagram Understanding in Geometry Questions

    Min Joon Seo, Hannaneh Hajishirzi, Ali Farhadi, and Oren EtzioniAAAI2014 Automatically solving geometry questions is a longstanding AI problem. A geometry question typically includes a textual description accompanied by a diagram. The first step in solving geometry questions is diagram understanding, which consists of identifying…
  • Discourse Complements Lexical Semantics for Non-factoid Answer Reranking

    Peter Jansen, Mihai Surdeanu, and Peter ClarkACL2014 We propose a robust answer reranking model for non-factoid questions that integrates lexical semantics with discourse information, driven by two representations of discourse: a shallow representation centered around discourse markers, and a deep one based on…
  • A Lightweight and High Performance Monolingual Word Aligner

    Xuchen Yao, Benjamin Van Durme, Chris Callision-Burch, and Peter ClarkACL2013 Fast alignment is essential for many natural language tasks. But in the setting of monolingual alignment, previous work has not been able to align more than one sentence pair per second. We describe a discriminatively trained monolingual word aligner that…
  • Automatic Coupling of Answer Extraction and Information Retrieval

    Xuchen Yao, Benjamin Van Durme, and Peter ClarkACL2013 Information Retrieval (IR) and Answer Extraction are often designed as isolated or loosely connected components in Question Answering (QA), with repeated overengineering on IR, and not necessarily performance gain for QA. We propose to tightly integrate them…
  • Answer Extraction as Sequence Tagging with Tree Edit Distance

    Xuchen Yao, Benjamin Van Durme, Chris Callision-Burch, and Peter ClarkNAACL2013 Our goal is to extract answers from preretrieved sentences for Question Answering (QA). We construct a linear-chain Conditional Random Field based on pairs of questions and their possible answer sentences, learning the association between questions and answer…
  • A Study of the Knowledge Base Requirements for Passing an Elementary Science Test

    Peter Clark, Phil Harrison, and Niranjan BalasubramanianCIKM • AKBC2013 Our long-term interest is in machines that contain large amounts of general and scientific knowledge, stored in a "computable" form that supports reasoning and explanation. As a medium-term focus for this, our goal is to have the computer pass a fourth-grade…
  • Extracting Meronyms for a Biology Knowledge Base Using Distant Supervision

    Xiao Ling, Dan Weld, and Peter ClarkAKBC2013 Knowledge of objects and their parts, meronym relations, are at the heart of many question-answering systems, but manually encoding these facts is impractical. Past researchers have tried hand-written patterns, supervised learning, and bootstrapped methods…
  • Learning Biological Processes with Global Constraints

    Aju Thalappillil Scaria, Jonathan Berant, Mengqiu Wang, Christopher D. Manning, Justin Lewis, Brittany Harding, and Peter ClarkEMNLP2013 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…