Search Results for author: Enrique Noriega-Atala

Found 8 papers, 0 papers with code

Neural-Guided Program Synthesis of Information Extraction Rules Using Self-Supervision

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.

Language Modelling Program Synthesis

A Human-machine Interface for Few-shot Rule Synthesis for Information Extraction

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.

Relation Extraction

Low Resource Causal Event Detection from Biomedical Literature

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.

Event Detection Knowledge Distillation +1

Neural Architectures for Biological Inter-Sentence Relation Extraction

no code implementations17 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.

Feature Engineering Relation +2

Understanding the Polarity of Events in the Biomedical Literature: Deep Learning vs. Linguistically-informed Methods

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.

Reading Comprehension

Learning what to read: Focused machine reading

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.

Reading Comprehension Reinforcement Learning (RL)

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