Sharing Semantic Resources

The Semantic Web is an extension of the current Web in which information, so far created for human consumption, becomes machine readable, “enabling computers and people to work in cooperation”. To turn into reality this vision several challenges are still open among which the most important is to share meaning formally represented with ontologies or more generally with semantic resources. This Semantic Web long-term goal has many convergences with the activities in the field of Human Language Technology and in particular in the development of Natural Language Processing applications where there is a great need of multilingual lexical resources. For instance, one of the most important lexical resources, WordNet, is also commonly regarded and used as an ontology. Nowadays, another important phenomenon is represented by the explosion of social collaboration, and Wikipedia, the largest encyclopedia in the world, is object of research as an up to date omni comprehensive semantic resource. The main topic of this thesis is the management and exploitation of semantic resources in a collaborative way, trying to use the already available resources as Wikipedia and Wordnet. This work presents a general environment able to turn into reality the vision of shared and distributed semantic resources and describes a distributed three-layer architecture to enable a rapid prototyping of cooperative applications for developing semantic resources

KYOTO: A System for Mining, Structuring, and Distributing Knowledge Across Languages and Cultures

We outline work performed within the framework of a current EC project. The goal is to construct a language-independent information system for a specific domain (environment/ecology/biodiversity) anchored in a language-independent ontology that is linked to wordnets in seven languages. For each language, information extraction and identification of lexicalized concepts with ontological entries is carried out by text miners (?Kybots?). The mapping of language-specific lexemes to the ontology allows for crosslinguistic identification and translation of equivalent terms. The infrastructure developed within this project enables long-range knowledge sharing and transfer across many languages and cultures, addressing the need for global and uniform transition of knowledge beyond the specific domains addressed here

Approaches towards a Lexical Web: the role of Interoperability

After highlighting some of the major dimensions that are relevant for Language Resources (LR) and contribute to their infrastructural role, I underline some priority areas of concern today with respect to implementing an open Language Infrastructure, and specifically what we could call a ?Lexical Web?. My objective is to show that it is imperative to define an underlying global strategy behind the set of initiatives which are/can be launched in Europe and world-wide, and that it is necessary an allembracing vision and a cooperation among different communities to achieve more coherent and useful results. I end up mentioning two new European initiatives that in this direction and promise to be influential in shaping the future of the LR area

A Web-based Architecture for Interoperability of Lexical Resources

In this paper we present aWeb Service Architecture for managing high level interoperability of Language Resources (LRs) by means of a Service Oriented Architecture (SOA) and the use of ISO standards, such as ISO LMF. We propose a layered architecture which separates the management of legacy resources (data collection) from data aggregation (workflow) and data access (user requests). We provide a case study to demonstrate how the proposed architecture is capable of managing data exchange among different lexical services in a coherent way and show how the use of a lexical standard becomes of primary importance when a protocol of interoperability is defined

D6.1: Technologies and Tools for Lexical Acquisition

This report describes the technologies and tools to be used for Lexical Acquisition in PANACEA. It includes descriptions of existing technologies and tools which can be built on and improved within PANACEA, as well as of new technologies and tools to be developed and integrated in PANACEA platform. The report also specifies the Lexical Resources to be produced. Four main areas of lexical acquisition are included: Subcategorization frames (SCFs), Selectional Preferences (SPs), Lexical-semantic Classes (LCs), for both nouns and verbs, and Multi-Word Expressions (MWEs)

Representation and Inference for Open-Domain Question Answering: Strength and Limits of two Italian Semantic Lexicons

La ricerca descritta nella tesi è stata dedicata alla costruzione di un prototipo di sistema di Question Answering per la lingua italiana. Il prototipo è stato utilizzato come ambiente di valutazione dell’utilità dell’informazione codificata in due lessici semantici computazionali, ItalWordNet e SIMPLE-CLIPS. Il fine è quello di metter in evidenza ipunti di forza e ilimiti della rappresentazione dell’informazione proposta dai due lessici