Translating Natural Language Sentences into ASP theories using SE-DCG grammars and Lambda Calculus Stefania Costantini and Alessio Paolucci Dip. di Informatica, Universit`a di L’Aquila, Coppito 67100, L’Aquila, Italy stefcost@di.univaq.it, alessiopaolucci@ieee.org Abstract. We build upon recent work by Baral, Dzifcal and Son that define the translation into ASP of (some classes of) natural language sentences from the lambda-calculus intermediate format generated by CCG grammars. We propose to use SE-DCG grammars, and we intro- duce automatic generation of lambda-calculus expressions from template ones, thus improving the effectiveness and generality of the translation process. 1 Introduction Many intelligent systems have to deal with knowledge expressed in natural lan- guage, either extracted from books, web pages and documents in general, or ex- pressed by human users. Knowledge acquisition from these sources is a challeng- ing matter, and many attempts are presently under way towards automatically translating natural language sentences into an appropriate knowledge represen- tation formalism [1]. The selection of a suitable formalism plays an important role but first-order logic, that would under many respects represent a natural choice, is actually not appropriate for expressing various kinds of knowledge, i.e., for dealing with default statements, normative statements with exceptions, etc. Recent work has investigated the usability of non-monotonic logics, like Answer Set Programming (ASP)[2]. The so-called Web 3.0 [3][4], despite its definition not well-established yet, makes the important assumption that applications should accept knowledge ex- pressed in a human-like form, transform it into a machine processable form and take this step as the basis for semantic applications. This bears a similarity with the Semantic Web objectives [4], though Web 3.0 is a much wider vision, where artificial intelligence techniques plays a central role. Also in the semantic web scenario however, automatically extracting semantic information from web pages or text documents requires to deal with natural language processing, and requires forms of reasoning. Translating natural language sentences into a logic knowledge representation is a key point on the applications side as well. In fact, designing applications such as semantic search engines implies obtaining a machine-processable form of the extracted knowledge that makes it possible to perform reasoning on the data so