About  the EXCITEMENT project 

There are two interleaved high-level goals for this project. The first is to set up, for the first time, a generic architecture and a comprehensive implementation for a multilingual textual inference platform and to make it available to the scientific and technological communities.

The second goal of the project is to develop a new generation of inference-based industrial text exploration applications for customer interactions, which will enable businesses to better analyze and make sense of their diverse and often unpredicted client content. These goals will be achieved for three languages – English, German and Italian, and for three customer interaction channels – speech (transcriptions), email and social media.



  • The EXCITEMENT project will be present at the HLT Projects Village which will be held during LREC 2014, 26-31 May 2014, Reykjavik, Iceland.

    In particular, the EXCITEMENT booth will present the EXCITEMENT Open Platform (EOP) .


  • 26 March 2014 - Release 1.1.1 of the EXCITEMENT Open Platform (EOP) is available at the following URL:


    The EOP  is a generic multi-lingual platform for textual inference made available to the scientific and technological communities.

    The major changes of release 1.1.2 compared to the previous release 1.1.1 concern BIUTEE EDA that now is provided with a new command-line  interface (for Linux) available through the BIUTEE environment. Then, the  new release fix the EOP v1.1.1 issue about "Wrong version of artifact  included" that could cause some strange errors when one uses EOP as a  library from their own code.

  • 2014

  • September 2-6, 2013 - A poster on the EXCITEMENT project was presented at MT Summit, which took place in Nice, France at the ACROPOLIS conference centre.


  • 3 December 2013 - Bernardo Magnini gave an invited talk at the 2nd Workshop on Argumentation in Artificial Intelligence and Philosophy: computational and philosophical perspectives (ARGAIP 2013), Turin (Italy). The title of the talk was ``Semantic Inferences in Natural Language Processing''.


Additional information