Search Results for author: Claire Bonial

Found 32 papers, 0 papers with code

InfoForager: Leveraging Semantic Search with AMR for COVID-19 Research

no code implementations DMR (COLING) 2020 Claire Bonial, Stephanie M. Lukin, David Doughty, Steven Hill, Clare Voss

This paper examines how Abstract Meaning Representation (AMR) can be utilized for finding answers to research questions in medical scientific documents, in particular, to advance the study of UV (ultraviolet) inactivation of the novel coronavirus that causes the disease COVID-19.

Domain Adaptation

What Can a Generative Language Model Answer About a Passage?

no code implementations EMNLP (MRQA) 2021 Douglas Summers-Stay, Claire Bonial, Clare Voss

Generative language models trained on large, diverse corpora can answer questions about a passage by generating the most likely continuation of the passage followed by a question/answer pair.

Language Modelling

The Search for Agreement on Logical Fallacy Annotation of an Infodemic

no code implementations LREC 2022 Claire Bonial, Austin Blodgett, Taylor Hudson, Stephanie M. Lukin, Jeffrey Micher, Douglas Summers-Stay, Peter Sutor, Clare Voss

We evaluate an annotation schema for labeling logical fallacy types, originally developed for a crowd-sourcing annotation paradigm, now using an annotation paradigm of two trained linguist annotators.

Logical Fallacies

Builder, we have done it: Evaluating & Extending Dialogue-AMR NLU Pipeline for Two Collaborative Domains

no code implementations IWCS (ACL) 2021 Claire Bonial, Mitchell Abrams, David Traum, Clare Voss

We adopt, evaluate, and improve upon a two-step natural language understanding (NLU) pipeline that incrementally tames the variation of unconstrained natural language input and maps to executable robot behaviors.

AMR Parsing Natural Language Understanding

Navigating to Success in Multi-Modal Human-Robot Collaboration: Analysis and Corpus Release

no code implementations26 Oct 2023 Stephanie M. Lukin, Kimberly A. Pollard, Claire Bonial, Taylor Hudson, Ron Arstein, Clare Voss, David Traum

Human-guided robotic exploration is a useful approach to gathering information at remote locations, especially those that might be too risky, inhospitable, or inaccessible for humans.

Dialogue-AMR: Abstract Meaning Representation for Dialogue

no code implementations LREC 2020 Claire Bonial, Lucia Donatelli, Mitchell Abrams, Stephanie M. Lukin, Stephen Tratz, Matthew Marge, Ron artstein, David Traum, Clare Voss

This paper describes a schema that enriches Abstract Meaning Representation (AMR) in order to provide a semantic representation for facilitating Natural Language Understanding (NLU) in dialogue systems.

Natural Language Understanding

Augmenting Abstract Meaning Representation for Human-Robot Dialogue

no code implementations WS 2019 Claire Bonial, Lucia Donatelli, Stephanie M. Lukin, Stephen Tratz, Ron artstein, David Traum, Clare Voss

We detail refinements made to Abstract Meaning Representation (AMR) that make the representation more suitable for supporting a situated dialogue system, where a human remotely controls a robot for purposes of search and rescue and reconnaissance.

Visual Understanding and Narration: A Deeper Understanding and Explanation of Visual Scenes

no code implementations31 May 2019 Stephanie M. Lukin, Claire Bonial, Clare R. Voss

We describe the task of Visual Understanding and Narration, in which a robot (or agent) generates text for the images that it collects when navigating its environment, by answering open-ended questions, such as 'what happens, or might have happened, here?'

Constructing an Annotated Corpus of Verbal MWEs for English

no code implementations COLING 2018 Abigail Walsh, Claire Bonial, Kristina Geeraert, John P. McCrae, Nathan Schneider, Clarissa Somers

This paper describes the construction and annotation of a corpus of verbal MWEs for English, as part of the PARSEME Shared Task 1. 1 on automatic identification of verbal MWEs.

Word Alignment

Can You Spot the Semantic Predicate in this Video?

no code implementations COLING 2018 Christopher Reale, Claire Bonial, Heesung Kwon, Clare Voss

We propose a method to improve human activity recognition in video by leveraging semantic information about the target activities from an expert-defined linguistic resource, VerbNet.

Human Activity Recognition Multi-Task Learning

Towards a Computational Lexicon for Moroccan Darija: Words, Idioms, and Constructions

no code implementations COLING 2018 Jamal Laoudi, Claire Bonial, Lucia Donatelli, Stephen Tratz, Clare Voss

In this paper, we explore the challenges of building a computational lexicon for Moroccan Darija (MD), an Arabic dialect spoken by over 32 million people worldwide but which only recently has begun appearing frequently in written form in social media.

Machine Translation

Automatically Extracting Qualia Relations for the Rich Event Ontology

no code implementations COLING 2018 Ghazaleh Kazeminejad, Claire Bonial, Susan Windisch Brown, Martha Palmer

Commonsense, real-world knowledge about the events that entities or {``}things in the world{''} are typically involved in, as well as part-whole relationships, is valuable for allowing computational systems to draw everyday inferences about the world.

Semantic Role Labeling World Knowledge

Object and Text-guided Semantics for CNN-based Activity Recognition

no code implementations4 May 2018 Sungmin Eum, Christopher Reale, Heesung Kwon, Claire Bonial, Clare Voss

We further improve upon the multitask learning approach by exploiting a text-guided semantic space to select the most relevant objects with respect to the target activities.

Human Activity Recognition Object Recognition

The Rich Event Ontology

no code implementations WS 2017 Susan Brown, Claire Bonial, Leo Obrst, Martha Palmer

In this paper we describe a new lexical semantic resource, The Rich Event On-tology, which provides an independent conceptual backbone to unify existing semantic role labeling (SRL) schemas and augment them with event-to-event causal and temporal relations.

Question Answering Semantic Role Labeling

Applying the Wizard-of-Oz Technique to Multimodal Human-Robot Dialogue

no code implementations10 Mar 2017 Matthew Marge, Claire Bonial, Brendan Byrne, Taylor Cassidy, A. William Evans, Susan G. Hill, Clare Voss

Our overall program objective is to provide more natural ways for soldiers to interact and communicate with robots, much like how soldiers communicate with other soldiers today.

Dialogue Management Management +1

Comprehensive and Consistent PropBank Light Verb Annotation

no code implementations LREC 2016 Claire Bonial, Martha Palmer

Recent efforts have focused on expanding the annotation coverage of PropBank from verb relations to adjective and noun relations, as well as light verb constructions (e. g., make an offer, take a bath).

PropBank: Semantics of New Predicate Types

no code implementations LREC 2014 Claire Bonial, Julia Bonn, Kathryn Conger, Jena D. Hwang, Martha Palmer

This research focuses on expanding PropBank, a corpus annotated with predicate argument structures, with new predicate types; namely, noun, adjective and complex predicates, such as Light Verb Constructions.

Machine Translation Sentence

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