- Ariel Gutman
- Alexandros Andre Chaaraoui
- Pascal Fleury
To engage users, a natural language generation system must produce grammatically correct and eloquent sentences. A simple NLG architecture may consist of a template repository coupled with a lexicon containing grammatically-annotated lexical expressions referring to the entities that are present in the domain of the system. The morphosyntactic features associated with these expressions are crucial to render grammatical and natural-sounding sentences. Existing electronic resources, like dictionaries or thesauri, lack wide-scale coverage of such referential expressions. In this work, we focus on the creation of a large-scale lexicon of referential expressions, relying on n-gram models, morpho-syntactic parsing, and non-linguistic knowledge. We describe the collected linguistic information and the techniques used to perform automatic extraction from large text corpora in a way that scales across languages and over millions of entities.
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