Manuela Sanguinetti

PartTUT: The Turin University Parallel Treebank

In this paper, we introduce an ongoing project for the development of a parallel treebank for Italian, English and French. The treebank is annotated in a dependency format, namely the one designed in the Turin University Treebank (TUT), hence the choice to call such new resource Par(allel)TUT. The project aims at creating a resource which can be useful in particular for translation research. Therefore, beyond constantly enriching the treebank with new and heterogeneous data, so as to build a dynamic and balanced multilingual treebank, the current stage of the project is devoted to the design of a tool for the alignment of data, which takes into account syntactic knowledge as annotated in this kind of resource. The paper focuses in particular on the study of translational divergences and their implications for the development of the alignment tool. The paper provides an overview of the treebank, with its current content and the peculiarities of the annotation format, the description of the classes of translational divergences which could be encountered in the treebank, together with a proposal for their alignment.

Developing corpora and tools for sentiment analysis: the experience of the University of Turin group

English. The paper describes the ongoing experience at the University of Turin in developing linguistic resources and tools for sentiment analysis of social media. We describe in particular the development of Senti-TUT, a human annotated corpus of Italian Tweets including labels for sentiment polarity and irony, which has been recently exploited within the SENTIment POLarity Classification shared task at Evalita 2014. Furthermore, we report about our ongoing work on the Felicittà web-based platform for estimating happiness in Italian cities, which provides visualization techniques to interactively explore the results of sentiment analysis performed over Italian geotagged Tweets. Italiano. L’articolo presenta l’esperienza fatta presso l’Università di Torino nello sviluppo di risorse linguistiche e strumenti per la sentiment analysis di social media. In particolare, viene descritto Senti-TUT, un corpus di Tweet in Italiano, che include annotazioni relative alla polarità del sentiment e alla presenza di ironia, utilizzato nell’ambito del task di SENTIment POLarity Classification di Evalita 2014. Inoltre viene presentato il lavoro su Felicittà, una piattaforma Web per la stima della felicità nelle città italiane, che fornisce diverse modalità di visualizzazione del grado di felicità che emerge da un’analisi del sentiment su messaggi Twitter geolocalizzati in

Converting the parallel treebank ParTUT in Universal StanfordDependencies

English. Assuming the increased need of language resources encoded with shared representation formats, the paper describes a project for the conversion of the multilingual parallel treebank ParTUT in the de facto standard of the Stanford Dependencies (SD) representation. More specifically, it reports the conversion process, currently implemented as a prototype, into the Universal SD format, more oriented to a cross-linguistic perspective and, therefore, more suitable for the purpose of our resource. Italiano. Considerando la crescente necessita di risorse linguistiche codificate in formati ampiamente condivisi, l’articolo presenta un progetto per la conversione di una risorsa multilingue annotata a livello sintattico nel formato, considerato uno standard de facto, delle Stanford Dependencies (SD). Piu precisamente l’articolo descrive il processo di conversione, di cui e attualmente sviluppato un prototipo, nelle Universal Stanford Dependencies, una versione delle SD maggiormente orientata a una prospettiva inter-linguistica e, per questo, particolarmente adatta agli scopi della nostra risorsa.