Accession Number:

AD1040958

Title:

Joint Probabilistic Reasoning About Coreference and Relations of Univeral Schema

Descriptive Note:

Technical Report,01 Oct 2012,01 May 2017

Corporate Author:

University of Massachusetts Amherst Hadley United States

Personal Author(s):

Report Date:

2017-10-01

Pagination or Media Count:

78.0

Abstract:

In this project, McCallums IESL lab at UMass Amherst researched and developed technologies for 1 automatic construction of knowledge bases from natural language text corpora, as well as 2 inference on these knowledge bases. Our work proposes and advances Universal Schema, which jointly learns embedded vector representations for the union of all input schema types relation types, entity types, and entities themselves, including those from existing knowledge bases such as Freebase and Wikipedia as well as relations and types in natural language textual patterns. We present techniques for relation and type prediction based on matrix factorization.

Subject Categories:

  • Computer Programming and Software

Distribution Statement:

APPROVED FOR PUBLIC RELEASE