RecallIE: Making Information Extraction Recall-aware

Anonymous

Nov 17, 2018 AKBC 2019 Conference Blind Submission readers: everyone Show Bibtex
  • Keywords: Information extraction, recall, completeness
  • TL;DR: Information extraction usually estimates precision but does not know about recall; we propose to fix this.
  • Abstract: Information extraction from text, IE for short, is the backbone of automated knowledge base construction. IE usually comes with precision estimates; however, it lacks awareness of recall. This paper introduces and discusses the issue of IE recall estimation and its practical importance. We present RecallIE, a methodology for estimating the possible recall from a given text segment. RecallIE uses distant supervision to estimate from language features whether a passage contains all objects for a given subject-predicate pair. We evaluate RecallIE across various granularities of text, and across various predicates. Our preliminary results indicate that estimating recall is a promising direction and technically feasible.
  • Archival status: Archival
  • Subject areas: Natural Language Processing, Information Extraction, Knowledge Representation
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