Natural Language as the Basis for Meaning Representation and Inference

Abstract. Semantic inference is an important component in many natural language understanding applications. Classical approaches to semantic inference rely on logical representations for meaning, which may be viewed as being "external" to the natural language itself. However, practical applications usually adopt shallower lexical or lexical-syntactic representations, which correspond closely to language structure. In many cases, such approaches lack a principled meaning representation and inference framework. We describe a generic semantic inference framework that operates directly on language-based structures, particularly syntactic trees. New trees are inferred by applying entailment rules, which provide a unified representation for varying types of inferences. Rules were generated by manual and automatic methods, covering generic linguistic structures as well as specific lexical-based inferences. Initial empirical evaluation in a Relation Extraction setting supports the va...

• Type: Conference
• Year: 2008
• Where: CICLING
• Authors: Ido Dagan, Roy Bar-Haim, Idan Szpektor, Iddo Greental, Eyal Shnarch
• Keywords: CICLING 2008, Generic Semantic Inference, Inference Framework, Natural Language Processing, Semantic Inference