A Rule-Based Unsupervised Morphology Learning Framework.

Constantine Lignos,Erwin Chan,Mitchell P. Marcus,Charles Yang

Conference and Labs of the Evaluation Forum (CLEF)（2009）

University of Pennsylvania

被引用32|浏览36

摘要

We use the Base and Transforms Model proposed by Chan [1] as the core of a morphological analyzer, extending its concept of base-derived relationships to allow multi-step derivations and adding a number of features required for robustness on larger corpora. The result is a rule-based morphological analyzer, attaining an F-score of 58.48% in English and 33.61% in German in the Morphochallenge 2009 Competition 1 evaluation.

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关键词

Language Modeling,Topic Modeling,Syntax-based Translation Models,Reinforcement Learning,Pretrained Models

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