From MultiJEDI to MOUSSE: Two ERC Projects for innovating multilingual disambiguation and semantic parsing of text

In this paper we present two interrelated projects funded by the European Research Council (ERC) aimed at addressing and over- coming the current limits of lexical semantics: MultiJEDI (Section 2) and MOUSSE (Section 4). We also present the results of Babelscape (Section 3), a Sapienza spin-off company with the goal of making the project outcomes sustainable in the long ter

Towards Generating Text from Discourse Representation Structures

International audienceWe argue that Discourse Representation Structures form a suitable level of language-neutral meaning representation for micro planning and surface realisation. DRSs can be viewed as the output of macro planning, and form the rough plan and structure for generating a text. We present the first ideas of building a large DRS corpus that enables the development of broad-coverage, robust text generators. A DRS-based generator imposes various challenges on micro-planning and surface realisation, including generating referring expressions , lexicalisation and aggregation

Reconstruction of the adult hemifacial microsomia patient with temporomandibular joint total joint prosthesis and orthognathic surgery

HFM patients' reconstruction has always been a challenge for maxillofacial surgeons, and numerous reconstructive techniques have been described. Surgical treatment depends on the patient's age and contemplates Temporomandibular Joint (TMJ) reconstruction in conjunction with orthognathic surgery, usually necessary following completion of growth to maximize the functional and esthetic results. Distraction osteogenesis had gained popularity as valid alternative in growing patients, but the two primary methods to reconstruct the TMJs involve the use of autogenous, using free or microvascular bone grafts, or alloplastic graft, but there is no widely accepted method

Building a General Knowledge Base of Physical Objects for Robots

Poster paperInternational audienceIn this paper we present an ongoing work on building a repository of knowledge about objects typically found in homes, their usual locations and usage. We extract an RDF knowledge base by automatically reading text on the Web and applying simple inference rules. The obtained common sense object relations are ready to be used in a domestic robotic setting, e.g. " a frying pan is usually located in the kitchen "

Building a General Knowledge Base of Physical Objects for Robots

Poster paperInternational audienceIn this paper we present an ongoing work on building a repository of knowledge about objects typically found in homes, their usual locations and usage. We extract an RDF knowledge base by automatically reading text on the Web and applying simple inference rules. The obtained common sense object relations are ready to be used in a domestic robotic setting, e.g. " a frying pan is usually located in the kitchen "

Towards Lifelong Object Learning by Integrating Situated Robot Perception and Semantic Web Mining

International audienceAutonomous robots that are to assist humans in their daily lives are required, among other things, to recognize and understand the meaning of task-related objects. However, given an open-ended set of tasks, the set of everyday objects that robots will encounter during their lifetime is not foreseeable. That is, robots have to learn and extend their knowledge about previously unknown objects on-the-job. Our approach automatically acquires parts of this knowledge (e.g., the class of an object and its typical location) in form of ranked hypotheses from the Semantic Web using contextual information extracted from observations and experiences made by robots. Thus, by integrating situated robot perception and Semantic Web mining, robots can continuously extend their object knowledge beyond perceptual models which allows them to reason about task-related objects , e.g., when searching for them, robots can infer the most likely object locations. An evaluation of the integrated system on long-term data from real office observations, demonstrates that generated hypotheses can effectively constrain the meaning of objects. Hence, we believe that the proposed system can be an essential component in a lifelong learning framework which acquires knowledge about objects from real world observations

Developing a large semantically annotated corpus

International audienceWhat would be a good method to provide a large collection of semantically annotated texts with formal, deep semantics rather than shallow? We argue that a bootstrapping approach comprising state-of-the-art NLP tools for parsing and semantic interpretation, in combination with a wiki-like interface for collaborative annotation of experts, and a game with a purpose for crowdsourcing, are the starting ingredients for fulfilling this enterprise. The result is a semantic resource that anyone can edit and that integrates various phenomena, including predicate-argument structure, scope, tense, thematic roles, rhetorical relations and presuppositions, into a single semantic formalism: Discourse Representation Theory. Taking texts rather than sentences as the units of annotation results in deep semantic representations that incorporate discourse structure and dependencies. To manage the various (possibly conflicting) annotations provided by experts and non-experts, we introduce a method that stores " Bits of Wisdom " in a database as stand-off annotations