Diplomatic parade or last struggle against fatalism? - Making sense of the Paris ministerial meeting on the Middle East Peace Process. EPC Commentary, 16 June 2016

On 3 June, the French government convened an international meeting in Paris, gathering 28 high-level delegations from all around the world, from Norway to Japan, in order to discuss the state of play and future prospects of the enduring Israel-Palestine conflict. The first ministerial meeting of the “Initiative for the Peace in the Middle East”, as it was labelled by the Quai d’Orsay, provided an important political signal, and a potential diplomatic format, to help revive the long-stalled peace process. Yet, its concrete deliverables remain beset by considerable uncertainty

A MWE Acquisition and Lexicon Builder Web Service

This paper describes the development of a web-service tool for the automatic extraction of Multi-word expressions lexicons, which has been integrated in a distributed platform for the automatic creation of linguistic resources. The main purpose of the work described is thus to provide a (computationally "light") tool that produces a full lexical resource: multi-word terms/items with relevant and useful attached information that can be used for more complex processing tasks and applications (e.g. parsing, MT, IE, query expansion, etc.). The output of our tool is a MW lexicon formatted and encoded in XML according to the Lexical Mark-up Framework. The tool is already functional and available as a service. Evaluation experiments show that the tool precision is of about 80%

KYOTO-LMF WordNet Representation Format

The format described in the following pages is the final revised proposal for representing wordnets inside the Kyoto project (henceforth "Kyoto-LMF wordnet format"). The reference model is Lexical Markup Framework (LMF), version 16, probably one of the most widely recognized standards for the representation of NLP lexicons. The goals of LMF are to provide a common model for the creation and use of such lexical resources, to manage the exchange of data between and among them, and to enable the merging of a large number of individual resources to form extensive global electronic respurces. LMF was specifically designed to accomodate as many models of lexical representations as possible. Purposefully, it is designed as a mea-model, i.e a high-level specification for lexical resources defining the structural constraints of a lexicon

Annotation of Toponyms in TEI Digital Literary Editions and Linking to the Web of Data

International audienceThis paper aims to discuss the challenges and benefits of the annotation of place names in literary texts and literary criticism. We shall first highlight the problems of encoding spatial information in digital editions using the TEI format by means of two manual annotation experiments and the discussion of various cases. This will lead to the question of how to use existing semantic web resources to complement and enrich toponym markup , in particular to provide mentions with precise geo-referencing. Finally the automatic annotation of a large corpus will show the potential of visualizing places from texts, by illustrating an analysis of the evolution of literary life from the spatial and geographical point of view.Este artigo aborda as dificuldades e as vantagens da anotação dos nomes de lugar em textos literários e de crítica literária. Começamos por realçar os problemas de codifi-cação da informação espacial em edições digitais usando o formato TEI, através de duas experiências de anotação manual e da análise de diversos casos. Isto conduzirá à questão de como utilizar os recursos da web semântica para complementar e enrique-cer a marcação de topónimos, em particular com georreferenciação rigorosa. Por último, a anotação automática de um grande corpus irá mostrar o potencial de visuali-zação de locais a partir de textos, ilustrando a análise da evolução da vida literária segundo um ponto de vista espacial e geográfico. Palavras-chave: estudos literários digitais; topónimos; web semântica; bases de dados geográficas; mapas e visualizações

Towards interfacing lexical and ontological resources

During the last two decades, the Computational Linguistics community has dedicated considerable effort to the research and development Lexical Resources (LRs), especially Computational Lexicons. These LRs, even though belonging to different linguistic approaches and theories, share a common element; all of them contain, explicitly or implicitly, an ontology as the means of organizing their structure

IMAGACT: Deriving an Action Ontology from Spoken Corpora

This paper presents the IMAGACT annotation infrastructure which uses both corpus - based and competence - based methods for the simultaneous extraction of a language independent Action ontology from English and Italian spontaneous speech corpora. The infrastructure relies on an innovative methodology based on images of prototypical scenes and will identify high frequency action concepts in everyday life, suitable for the implementation of an open set of languages

Leveraging a Narrative Ontology to Query a Literary Text

In this work we propose a model for the representation of the narrative of a literary text. The model is structured in an ontology and a lexicon constituting a knowledge base that can be queried by a system. This narrative ontology, as well as describing the actors, locations, situations found in the text, provides an explicit formal representation of the timeline of the story. We will focus on a specific case study, that of the representation of a selected portion of Homer\u27s Odyssey, in particular of the knowledge required to answer a selection of salient queries, formulated by a literary scholar. This work is being carried out within the framework of the Semantic Web by adopting models and standards such as RDF, OWL, SPARQL, and lemon among others

Presenting a System of Human-Machine Interaction for Performing Map Tasks

A system for human machine interaction is presented, that offers second language learners of Italian the possibility of assessing their competence by performing a map task, namely by guiding the a virtual follower through a map with written instructions in natural language. The underlying natural language processing algorithm is described, and the map authoring infrastructure is presented

D6.2 Integrated Final Version of the Components for Lexical Acquisition

The PANACEA project has addressed one of the most critical bottlenecks that threaten the development of technologies to support multilingualism in Europe, and to process the huge quantity of multilingual data produced annually. Any attempt at automated language processing, particularly Machine Translation (MT), depends on the availability of language-specific resources. Such Language Resources (LR) contain information about the language\u27s lexicon, i.e. the words of the language and the characteristics of their use. In Natural Language Processing (NLP), LRs contribute information about the syntactic and semantic behaviour of words - i.e. their grammar and their meaning - which inform downstream applications such as MT. To date, many LRs have been generated by hand, requiring significant manual labour from linguistic experts. However, proceeding manually, it is impossible to supply LRs for every possible pair of European languages, textual domain, and genre, which are needed by MT developers. Moreover, an LR for a given language can never be considered complete nor final because of the characteristics of natural language, which continually undergoes changes, especially spurred on by the emergence of new knowledge domains and new technologies. PANACEA has addressed this challenge by building a factory of LRs that progressively automates the stages involved in the acquisition, production, updating and maintenance of LRs required by MT systems. The existence of such a factory will significantly cut down the cost, time and human effort required to build LRs. WP6 has addressed the lexical acquisition component of the LR factory, that is, the techniques for automated extraction of key lexical information from texts, and the automatic collation of lexical information into LRs in a standardized format. The goal of WP6 has been to take existing techniques capable of acquiring syntactic and semantic information from corpus data, improving upon them, adapting and applying them to multiple languages, and turning them into powerful and flexible techniques capable of supporting massive applications. One focus for improving the scalability and portability of lexical acquisition techniques has been to extend exiting techniques with more powerful, less "supervised" methods. In NLP, the amount of supervision refers to the amount of manual annotation which must be applied to a text corpus before machine learning or other techniques are applied to the data to compile a lexicon. More manual annotation means more accurate training data, and thus a more accurate LR. However, given that it is impractical from a cost and time perspective to manually annotate the vast amounts of data required for multilingual MT across domains, it is important to develop techniques which can learn from corpora with less supervision. Less supervised methods are capable of supporting both large-scale acquisition and efficient domain adaptation, even in the domains where data is scarce. Another focus of lexical acquisition in PANACEA has been the need of LR users to tune the accuracy level of LRs. Some applications may require increased precision, or accuracy, where the application requires a high degree of confidence in the lexical information used. At other times a greater level of coverage may be required, with information about more words at the expense of some degree of accuracy. Lexical acquisition in PANACEA has investigated confidence thresholds for lexical acquisition to ensure that the ultimate users of LRs can generate lexical data from the PANACEA factory at the desired level of accuracy