Antonella Bristot

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The system for semantic evaluation VENSES (Venice Semantic Evaluation System) is organized as a pipeline of two subsystems: the first is a reduced version of GETARUN, our system for Text Understanding. The output of the system is a flat list of head-dependent structures (HDS) with Grammatical Relations (GRs) and Semantic Roles (SRs) labels. The evaluation(More)
The VENEX corpus is a corpus of Italian annotated with information about anaphora and deixis, created in a joint project between the Università di Venezia and the University of Essex. The corpus includes both texts (articles from a financial newspaper) and dialogues (an Italian version of the MapTask corpus). The annotation scheme is an almost complete(More)
We present VENSES, a linguistically-based approach for semantic inference which is built around a neat division of labour between two main components: a grammatically-driven subsystem which is responsible for the level of predicate-arguments well-formedness and works on the output of a deep parser that produces augmented head-dependency structures. A second(More)
In this paper we will present an evaluation of current state-of-the-art algorithms for Anaphora Resolution based on a segment of Susanne corpus (itself a portion of Brown Corpus), a much more comparable text type to what is usually required at an international level for s u c h a p p l i c a t i o n d o m a i n s a s Question/Answering, Information(More)
In this paper we will describe VIT (Venice Italian Treebank), created at the University of Venice. We will focus on the syntactic-semantic features and on the quantitative analysis of the data of our treebank comparing them to other treebanks. In general, we will try to substantiate the claim that treebanking grammars or parsers is dramatically dependent on(More)
In this paper we will present work carried out to scale up the system for text understanding called GETARUNS, and port it to be used in dialogue understanding. The current goal is that of extracting automatically argumentative information in order to build argumentative structure. The long term goal is using argumentative structure to produce automatic(More)
In this paper we will present work carried out to scale up the system for text understanding called GETARUNS, and port it to be used in dialogue understanding. We will present the adjustments we made in order to cope with transcribed spoken dialogues like those produced in the ICSI Berkely project. In a final section we present preliminary evaluation of the(More)
summarization of conversations is a very challenging task that requires full understanding of the dialog turns, their roles and relationships in the conversations. We present an efficient system, derived from a full-fledged text analysis system, that performs the necessary linguistic analysis of turns in conversations and provides useful argumentative(More)
In this paper we propose a rule-based approach to extract dependency and grammatical relations from the Venice Italian Treebank (VIT) (Delmonte et al., 2007) with bracketed tree structure. To our knowledge, the only dependency annotated corpus for Italian available is the Turin University Treebank (Lesmo et al., 2002), which has 25,000 tokens and is about(More)
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