Work

CogCompTime: A Tool for Understanding Time in Natural Language

Year: 2018

Type: conference-paper

Abstract: Automatic extraction of temporal information is important for natural language understanding.It involves two basic tasks: (1) Understanding time expressions that are mentioned explicitly in text (e.g., February 27, 1998 or tomorrow), and (2) Understanding temporal information that is conveyed implicitly via relations.This paper introduces CogCompTime, a system that has these two important functionalities.It incorporates the most recent progress, achieves state-of-the-art performance, and is publicly available.1 We believe that this demo will provide valuable insight for temporal understanding and be useful for multiple time-aware applications.

Source: Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP)

DOI: 10.18653/v1/d18-2013

Authors: Qiang Ning, Ben Zhou, Zhili Feng, Haoruo Peng, Dan Roth

Institutions: University of Illinois Urbana-Champaign, University of Wisconsin–Madison, University of Pennsylvania

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Center for Cognitive Computing Systems Research, Allen Institute for Artificial Intelligence, Army Research Laboratory

Awards: G5176188519, G5259331294, G948678646