Propminer: A Workflow for Interactive Information Extraction and Exploration using Dependency Trees

نویسندگان

  • Alan Akbik
  • Oresti Konomi
  • Michail Melnikov
چکیده

The use of deep syntactic information such as typed dependencies has been shown to be very effective in Information Extraction. Despite this potential, the process of manually creating rule-based information extractors that operate on dependency trees is not intuitive for persons without an extensive NLP background. In this system demonstration, we present a tool and a workflow designed to enable initiate users to interactively explore the effect and expressivity of creating Information Extraction rules over dependency trees. We introduce the proposed five step workflow for creating information extractors, the graph query based rule language, as well as the core features of the PROPMINER tool.

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تاریخ انتشار 2013