Manuela Speranza

Ontology and the Lexicon: Merging global and specialized linguistic ontologies

There is an increasing interest in linguistic ontologies (e.g. WordNet) for a variety of content-based tasks, including conceptual indexing, word sense disambiguation and cross-language information retrieval. A relevant contribution in this direction is represented by linguistic ontologies with domain specific coverage, which are a crucial topic for the development of concrete application systems. This paper tries to go a step further in the direction of the interoperability of specialized linguistic ontologies, by addressing the problem of their integration with global ontologies. This scenario poses some simplifications with respect to the general problem of merging ontologies, since it enables to define a strong precedence criterion so that terminological information overshadows generic information whenever conflicts arise. We assume the EuroWordNet model and propose a methodology to “plug” specialized linguistic ontologies into global ontologies. Experimental data related to an implemented algorithm, which has been tested on a global and a specialized linguistic ontology for the Italian language, are provided.

A semantic-based approach to interoperability of classification hierarchies: evaluation of linguistic techniques

Classification Hierarchies (CHs) are widely used to organize documents in a way that makes their retrieval casier. Common examples of CHs are Web directories, marketplace catalogs, and file systems. In this paper we discuss and evaluate CtxMatch, an approach to interoperability that discovers mappings among CHs considering the semantic interpretation of their nodes. CtxMatch performs a linguistic processing of the labels attached to the nodes, including tokenization, Part of Speech tagging, multiword recognition and word sense disambiguation. We present an evaluation of the overall performance of the approach over Web directories as well as a systematic analysis of the linguistic modules involved.

SemEval-2015 Task 4: TimeLine: Cross-Document Event Ordering

This paper describes the outcomes of the TimeLine task (Cross-Document Event Ordering), that was organised within the Time and Space track of SemEval-2015. Given a set of documents and a set of target entities, the task consisted of building a timeline for each entity, by detecting, anchoring in time and ordering the events involving that entity. The TimeLine task goes a step further than previous evaluation challenges by requiring participant systems to perform both event coreference and temporal relation extraction across documents. Four teams submitted the output of their systems to the four proposed subtracks for a total of 13 runs, the best of which obtained an F1-score of 7.85 in the main track (timeline creation from raw text).

The EVALITA 2016 Event Factuality Annotation Task (FactA)

This paper describes the design and reports the results of two questionnaires. The first of these questionnaires was created to collect information about the interest of industrial companies in the field of Italian text/speech analytics towards the evaluation campaign EVALITA; the second to gather comments and suggestions for the future of the evaluation and of its final workshop from the participants and the organizers of the campaign on the last two editions (2011 and 2014). Novelties introduced in the organization of EVALITA 2016 on the basis of the questionnaires results are also reported.

Making Explicit the Hidden Semantics of Hierarchical Classifications

Hierarchical classifications are concept hierarchies used to organize large amounts of documents. File systems, products’ taxonomies for the market place and the directories provided by Web portals are common examples of hierarchical classifications. We propose a methodology for building a semantic interpretation of hierarchical classifications on the basis of the analysis of the taxonomic relations and the linguistic material they contain. We provide a formal semantics for hierarchical classifications and use it to interpret the implicit knowledge represented. Relevant phenomena addressed include the disambiguation of polysemous words, the semantics of multiwords, and the interpretation of coordinations. We report about experiments performed on the Web Directories of Google and Yahoo!.

The Scope and Focus of Negation: A Complete Annotation Framework for Italian

In this paper we present a complete framework for the annotation of negation in Italian, which accounts for both negation scope and negation focus, and also for language-specific phenomena such as negative concord. In our view, the annotation of negation complements more comprehensive Natural Language Processing tasks, such as temporal information processing and sentiment analysis. We applied the proposed framework and the guidelines built on top of it to the annotation of written texts, namely news articles and tweets, thus producing annotated data for a total of over 36,000 tokens.

Named Entity Recognition on Transcribed Broadcast News at EVALITA 2011

This paper describes features and outcomes of the Named Entity Recognition on Transcribed Broadcast News task at EVALITA 2011. This task represented a change with respect to previous editions of the NER task within the EVALITA evaluation campaign because it was based on automatic transcription of spoken broadcast news. In this paper, we present the training and test data used, the evaluation procedure and participants’ results. In particular, three participating systems are described and the results they obtained are discussed; special attention is given to the analysis of the impact of transcription errors on NER performance.