The paper introduces an ongoing project for the development of a parallel treebank for Italian, English and French, i.e. Parallel--TUT, or simply ParTUT. For the development of this resource, both the dependency and constituency-based formats of the Italian Turin University Treebank (TUT) have been applied to a preliminary dataset, which includes the whole text of the Universal Declaration of Human Rights, and sentences from the JRC-Acquis Multilingual Parallel Corpus and the Creative Commons licence. The focus of the project is mainly on the quality of the annotation and the investigation of some issues related to the alignment of data that can be allowed by the TUT formats, also taking into account the availability of conversion tools for display data in standard ways, such as Tiger--XML and CoNLL formats. It is, in fact, our belief that increasing the portability of our treebank could give us the opportunity to access resources and tools provided by other research groups, especially at this stage of the project, where no particular tool -- compatible with the TUT format -- is available in order to tackle the alignment problems.

As the interest of the NLP community grows to develop several treebanks also for languages other than English, we observe efforts towards evaluating the impact of different annotation strategies used to represent particular languages or with reference to particular tasks. This paper contributes to the debate on the influence of resources used for the training and development on the performance of parsing systems. It presents a comparative analysis of the results achieved by three different dependency parsers developed and tested with respect to two treebanks for the Italian language, namely TUT and ISST--TANL, which differ significantly at the level of both corpus composition and adopted dependency representations.

The EVALITA 2007 Parsing Task has been the first contest among parsing systems for Italian. It is the first attempt to compare the approaches and the results of the existing parsing systems specific for this language using a common treebank annotated using both a dependency and a constituency-based format. The development data set for this parsing competition was taken from the Turin University Treebank, which is annotated both in dependency and constituency format. The evaluation metrics were those standardly applied in CoNLL and PARSEVAL. The results of the parsing results are very promising and higher than the state-of-the-art for dependency parsing of Italian. An analysis of such results is provided, which takes into account other experiences in treebank-driven parsing for Italian and for other Romance languages (in particular, the CoNLL X & 2007 shared tasks for dependency parsing). It focuses on the characteristics of data sets, i.e. type of annotation and size, parsing paradigms and approaches applied also to languages other than Italian.

This paper introduces a number theoretical and practical issues related to the “Syllabus”. Syllabusis a multi-lingua ontology based tool, designed to improve the applications of the European Directives in the various European countries.

This paper describes an approach to Natural Language access to databases based on ontologies. Their role is to make the central part of the translation process independent both of the specific language and of the particular database schema. The input sentence is parsed and the parse tree is semantically annotated via references to the ontology describing the application. This first step is, of course, language dependent: the parsing process depends on the syntax of the language and the annotation depends on the meaning of words, expressed as links between words and concepts in the ontology. Then, the annotated tree is used to produce an “ontological query”, i.e. a query expressed in terms of paths on the ontology. This second step is entirely language- and DB-independent. Finally, the ontological query is translated into a standard SQL query, on the basis of a concept-to-DB mapping, specifying how each concept and relation is mapped onto the database.

The working assumption is that cognitive modeling of NLP and engineering solutions to free text parsing can converge to optimal parsing. The claim of the paper is that the methodology to achieve such a result is to develop a concrete environment with a flexible parser, that allows the testing of various psycholinguistic strategies on real texts. In this paper we outline a flexible parser based on a dependency grammar.