Impact of Machine-Translated Text on Entity and Relationship Extraction

Abstract

We performed an experiment to study the effects of machine (performed by software) versus manual (performed by a human) translation on the performance of a Small Business Innovation Research text analytics tool. The text analytics in the experiment is Contour, developed by Decisive Analytics Corporation, which automatically builds high-fidelity social networks from text data sets too large to be scrutinized in detail through manual effort. Specifically, we analyzed the ability to extract text entities with the roles of person, location, or organization. The data consists of the translations of many news stories collected from Arabic language websites. There are 5 translations for each story to examine (4 human and 1 machine). The performance of the machine translation Contour results is analyzed against the Contour results of the manual translation

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2014
Accession Number
ADA616866

Entities

People

  • John T. Richardson
  • Mark R. Mittrick

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Arabic Language
  • Artificial Intelligence Computing
  • Commerce
  • Corporations
  • Data Sets
  • Extraction
  • Foreign Languages
  • Language
  • Machine Translation
  • Military Research
  • Named Entity Recognition
  • Small Business
  • Social Media
  • Social Networks
  • Text Analytics
  • Translations

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Computer Science.
  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation