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Building a generic debugger for information extraction pipelines

Published: 24 October 2011 Publication History

Abstract

Complex information extraction (IE) pipelines are becoming an integral component of most text processing frameworks. We introduce a first system to help IE users analyze extraction pipeline semantics and operator transformations interactively while debugging. This allows the effort to be proportional to the need, and to focus on the portions of the pipeline under the greatest suspicion. We present a generic debugger for running post-execution analysis of any IE pipeline consisting of arbitrary types of operators. For this, we propose an effective provenance model for IE pipelines which captures a variety of operator types, ranging from those for which full to no specifications are available. We have evaluated our proposed algorithms and provenance model on large-scale real-world extraction pipelines.

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Cited By

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  • (2013)Information extraction as a filtering taskProceedings of the 22nd ACM international conference on Information & Knowledge Management10.1145/2505515.2505557(2049-2058)Online publication date: 27-Oct-2013
  • (2013)Automatic pipeline construction for real-time annotationProceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I10.1007/978-3-642-37247-6_4(38-49)Online publication date: 24-Mar-2013

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  1. Building a generic debugger for information extraction pipelines

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    cover image ACM Conferences
    CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
    October 2011
    2712 pages
    ISBN:9781450307178
    DOI:10.1145/2063576
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 24 October 2011

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    1. information extraction
    2. provenance

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    • (2013)Information extraction as a filtering taskProceedings of the 22nd ACM international conference on Information & Knowledge Management10.1145/2505515.2505557(2049-2058)Online publication date: 27-Oct-2013
    • (2013)Automatic pipeline construction for real-time annotationProceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I10.1007/978-3-642-37247-6_4(38-49)Online publication date: 24-Mar-2013

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