Generating a Morphological Lexicon of Organization Entity Names

This paper describes methods used for generating a morphological lexicon of organization entity names in Croatian. This resource is intended for two primary tasks: template-based natural language generation and named entity identification. The main problems concerning the lexicon generation are high level of inflection in Croatian and low linguistic quality of the primary resource containing named entities in normal form. The problem is divided into two subproblems concerning single-word and multi-word expressions. The ord problem is solved by training a supervised learning algorithm called linear successive abstraction. With existing common language morphological resources and two simple hand-crafted rules backing up the algorithm, accuracy of 98.70% on the test set is achieved. The multi-word problem is solved through a semi-automated process for multi-word entities occurring in the first 10,000 named entities. The generated multi-word lexicon will be used for natural language gener...

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Nikola Ljubesic, Tomislava Lauc, Damir Boras
• Keywords: Education, Entity Identification, Lexicon, LREC 2008, Natural Language Generation