A Logic-based Approach for Recognizing Textual Entailment Supported by Ontological Background Knowledge

We present the architecture and the evaluation of a new system for recognizing textual entailment (RTE). In RTE we want to identify automatically the type of a logical relation between two input texts. In particular, we are interested in proving the existence of an entailment between them. We conceive our system as a modular environment allowing for a high-coverage syntactic and semantic text analysis combined with logical inference. For the syntactic and semantic analysis we combine a deep semantic analysis with a shallow one supported by statistical models in order to increase the quality and the accuracy of results. For RTE we use logical inference of first-order employing model-theoretic techniques and automated reasoning tools. The inference is supported with problem-relevant background knowledge extracted automatically and on demand from external sources like, e.g., WordNet, YAGO, and OpenCyc, or other, more experimental sources with, e.g., manually defined presupposition resolutions, or with axiomatized general and common sense knowledge. The results show that fine-grained and consistent knowledge coming from diverse sources is a necessary condition determining the correctness and traceability of results.Comment: 25 pages, 10 figure

Natural language semantics and compiler technology

This paper recommends an approach to the implementation of semantic representation languages (SRLs) which exploits a parallelism between SRLs and programming languages (PLs). The design requirements of SRLs for natural language are similar to those of PLs in their goals. First, in both cases we seek modules in which both the surface representation (print form) and the underlying data structures are important. This requirement highlights the need for general tools allowing the printing and reading of expressions (data structures). Second, these modules need to cooperate with foreign modules, so that the importance of interface technology (compilation) is paramount; and third, both compilers and semantic modules need "inferential" facilities for transforming (simplifying) complex expressions in order to ease subsequent processing. But the most important parallel is the need in both fields for tools which are useful in combination with a variety of concrete languages -- general purpose parsers, printers, simplifiers (transformation facilities) and compilers. This arises in PL technology from (among other things) the need for experimentation in language design, which is again parallel to the case of SRLs. Using a compiler-based approach, we have implemented NLL, a public domain software package for computational natural language semantics. Several interfaces exist both for grammar modules and for applications, using a variety of interface technologies, including especially compilation. We review here a variety of NLL, applications, focusing on COSMA, an NL interface to a distributed appointment manager

GATE -- an Environment to Support Research and Development in Natural Language Engineering

We describe a software environment to support research and development in natural language (NL) engineering. This environment -- GATE (General Architecture for Text Engineering) -- aims to advance research in the area of machine processing of natural languages by providing a software infrastructure on top of which heterogeneous NL component modules may be evaluated and refined individually or may be combined into larger application systems. Thus, GATE aims to support both researchers and developers working on component technologies (e.g. parsing, tagging, morphological analysis) and those working on developing end-user applications (e.g. information extraction, text summarisation, document generation, machine translation, and second language learning). GATE will promote reuse of component technology, permit specialisation and collaboration in large-scale projects, and allow for the comparison and evaluation of alternative technologies. The first release of GATE is now available

On explaining “Explanations”

What is an explanation? The popular responses are: We can explain what a word means, how to run a computer programme, why John decided to marry Jane, and even historical facts like the extinction of the dinosaurs. But what about explananda such as the linguistic entity “Who saw John?”. The paper surveys a spectrum of responses, some theory-free, others theory-bound. For all of these, we employ the six Dimensions of explanation

SemTAG, the LORIA toolbox for TAG-based Parsing and Generation

In this paper, we introduce SemTAG, a toolbox for TAG-based parsing and generation. This environment supports the development of wide-coverage grammars and differs from existing environments for TAG such as XTAG, in that it includes a semantic dimension. SemTAG is open-source and freely available