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A Hybrid Entity-Mention Pronoun Resolution Model for German Using Markov Logic Networks


Tuggener, Don; Klenner, Manfred (2014). A Hybrid Entity-Mention Pronoun Resolution Model for German Using Markov Logic Networks. In: KONVENS 2014, Hildesheim, 8 October 2014 - 10 October 2014. s.n., 21-29.

Abstract

This paper presents a hybrid pronoun resolution system for German. It uses a simple rule-driven entity-mention formalism to incrementally process discourse entities. Antecedent selection is performed based on Markov Logic Networks (MLNs). The hybrid architecture yields a cheap problem formulation in the MLNs w.r.t. inference complexity but pertains their expressiveness. We compare the system to a rule-driven baseline and an extension which uses a memory-based learner. We find that the MLN hybrid outperforms its competitors by large margins.

Abstract

This paper presents a hybrid pronoun resolution system for German. It uses a simple rule-driven entity-mention formalism to incrementally process discourse entities. Antecedent selection is performed based on Markov Logic Networks (MLNs). The hybrid architecture yields a cheap problem formulation in the MLNs w.r.t. inference complexity but pertains their expressiveness. We compare the system to a rule-driven baseline and an extension which uses a memory-based learner. We find that the MLN hybrid outperforms its competitors by large margins.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Uncontrolled Keywords:Coreference Resolution Pronoun Resolution
Language:English
Event End Date:10 October 2014
Deposited On:16 Oct 2014 21:22
Last Modified:20 Aug 2021 07:22
Publisher:s.n.
ISBN:3-934105-46-7
OA Status:Green

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