Search Results for author: Susan Windisch Brown

Found 7 papers, 2 papers with code

SemLink 2.0: Chasing Lexical Resources

1 code implementation IWCS (ACL) 2021 Kevin Stowe, Jenette Preciado, Kathryn Conger, Susan Windisch Brown, Ghazaleh Kazeminejad, James Gung, Martha Palmer

The SemLink resource provides mappings between a variety of lexical semantic ontologies, each with their strengths and weaknesses.

A Graphical Interface for Curating Schemas

no code implementations ACL 2021 Piyush Mishra, Akanksha Malhotra, Susan Windisch Brown, Martha Palmer, Ghazaleh Kazeminejad

Much past work has focused on extracting information like events, entities, and relations from documents.

RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System

1 code implementation NAACL 2021 Haoyang Wen, Ying Lin, Tuan Lai, Xiaoman Pan, Sha Li, Xudong Lin, Ben Zhou, Manling Li, Haoyu Wang, Hongming Zhang, Xiaodong Yu, Alexander Dong, Zhenhailong Wang, Yi Fung, Piyush Mishra, Qing Lyu, D{\'\i}dac Sur{\'\i}s, Brian Chen, Susan Windisch Brown, Martha Palmer, Chris Callison-Burch, Carl Vondrick, Jiawei Han, Dan Roth, Shih-Fu Chang, Heng Ji

We present a new information extraction system that can automatically construct temporal event graphs from a collection of news documents from multiple sources, multiple languages (English and Spanish for our experiment), and multiple data modalities (speech, text, image and video).

Coreference Resolution Event Extraction

VerbNet Representations: Subevent Semantics for Transfer Verbs

no code implementations WS 2019 Susan Windisch Brown, Julia Bonn, James Gung, Annie Zaenen, James Pustejovsky, Martha Palmer

This paper announces the release of a new version of the English lexical resource VerbNet with substantially revised semantic representations designed to facilitate computer planning and reasoning based on human language.

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.

Natural Language Processing Semantic Role Labeling

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