Symbolic Learning of Rules for Semantic Relation Types Identification in French Genitive Postnominal Prepositional Phrases

Abstract

We are interested in the semantic relations conveyed by polylexical entities in the postnominal prepositional noun phrases form “A de B” (A of B). After identifying a relevant set of semantic relations types, we proceed, using generative AI, to build a collection of phrases, for each semantic relation type identified. We propose an algorithm for creating rules that allow the selection of the relation between A and B in noun phrases of each type. These rules correspond to selecting from a knowledge base the appropriate neighborhood of a given term. For the phrase “désert d’Algérie” carrying the location relation, the term “désert” is identified as a geographical location, and “Algérie” as a country. These constraints are used to automatically learn a set of rules for selecting the location relation for this type of example. Rules are not exclusive as there may be instances that fall under multiple relations. In the phrase “portrait de sa mère - the portrait of his/her mother”, all of depiction, possession, and producer types are a possible match.

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