ONTOGENERATION: Reusing Domain and Linguistic Ontologies for Spanish Text Generation

A significant problem facing the reuse of ontologies is to make their content more widely accessible to any potential user. Wording all the information represented in an ontology is the best way to ease the retrieval and understanding of its contents. This article proposes a general approach to reuse domain and linguistic ontologies with natural language generation technology, describing a practical system for the generation of Spanish texts in the domain of chemical substances. For this purpose the following steps have been taken: (a) an ontology in the chemicals domain developed under the METHONTOLOGY framework and the Ontology Design Environment (ODE) has been taken as knowledge source; (b) the linguistic ontology GUM (Generalized Upper Model) used in other languages has been extended and modified for Spanish; (c) a Spanish grammar has been built following the systemic-functional model by using the KPML (Komet-Penman Multilingual) environment. As result, the final system named Ontogeneration permits the user to consult and retrieve all the information of the ontology in Spanish

A Flexible Shallow Approach to Text Generation

In order to support the efficient development of NL generation systems, two orthogonal methods are currently pursued with emphasis: (1) reusable, general, and linguistically motivated surface realization components, and (2) simple, task-oriented template-based techniques. In this paper we argue that, from an application-oriented perspective, the benefits of both are still limited. In order to improve this situation, we suggest and evaluate shallow generation methods associated with increased flexibility. We advise a close connection between domain-motivated and linguistic ontologies that supports the quick adaptation to new tasks and domains, rather than the reuse of general resources. Our method is especially designed for generating reports with limited linguistic variations.Comment: LaTeX, 10 page

A System for Automatic English Text Expansion

This work was supported in part by the Mineco, Spain, under Grant TEC2016-76465-C2-2-R, in part by the Xunta de Galicia, Spain, under Grant GRC-2018/53 and Grant ED341D R2016/012, and in part by the University of Vigo Travel Grant to visit the CLAN Research Group, University of Aberdeen, U.K.Peer reviewedPublisher PD