no code implementations • PANDL (COLING) 2022 • Enrique Noriega-Atala, Robert Vacareanu, Gus Hahn-Powell, Marco A. Valenzuela-Escárcega
We propose a neural-based approach for rule synthesis designed to help bridge the gap between the interpretability, precision and maintainability exhibited by rule-based information extraction systems with the scalability and convenience of statistical information extraction systems.
no code implementations • NAACL (ACL) 2022 • Robert Vacareanu, George C.G. Barbosa, Enrique Noriega-Atala, Gus Hahn-Powell, Rebecca Sharp, Marco A. Valenzuela-Escárcega, Mihai Surdeanu
We propose a system that assists a user in constructing transparent information extraction models, consisting of patterns (or rules) written in a declarative language, through program synthesis. Users of our system can specify their requirements through the use of examples, which are collected with a search interface. The rule-synthesis system proposes rule candidates and the results of applying them on a textual corpus; the user has the option to accept the candidate, request another option, or adjust the examples provided to the system. Through an interactive evaluation, we show that our approach generates high-precision rules even in a 1-shot setting.
no code implementations • BioNLP (ACL) 2022 • Zhengzhong Liang, Enrique Noriega-Atala, Clayton Morrison, Mihai Surdeanu
Recognizing causal precedence relations among the chemical interactions in biomedical literature is crucial to understanding the underlying biological mechanisms.
no code implementations • NAACL (SUKI) 2022 • Enrique Noriega-Atala, Mihai Surdeanu, Clayton T. Morrison
We propose a method to teach an automated agent to learn how to search for multi-hop paths of relations between entities in an open domain.
no code implementations • 17 Dec 2021 • Enrique Noriega-Atala, Peter M. Lovett, Clayton T. Morrison, Mihai Surdeanu
We introduce a family of deep-learning architectures for inter-sentence relation extraction, i. e., relations where the participants are not necessarily in the same sentence.
no code implementations • WS 2019 • Enrique Noriega-Atala, Zhengzhong Liang, John Bachman, Clayton Morrison, Mihai Surdeanu
An important task in the machine reading of biochemical events expressed in biomedical texts is correctly reading the polarity, i. e., attributing whether the biochemical event is a promotion or an inhibition.
no code implementations • 14 Dec 2018 • Enrique Noriega-Atala, Paul D. Hein, Shraddha S. Thumsi, Zechy Wong, Xia Wang, Clayton T. Morrison
We present an analysis of the problem of identifying biological context and associating it with biochemical events in biomedical texts.
no code implementations • EMNLP 2017 • Enrique Noriega-Atala, Marco A. Valenzuela-Escarcega, Clayton T. Morrison, Mihai Surdeanu
In this work, we introduce a focused reading approach to guide the machine reading of biomedical literature towards what literature should be read to answer a biomedical query as efficiently as possible.