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%

Using LMF to Shape a Lexicon for the Biomedical Domain

This paper describes the design, implementation and population of the BioLexicon in the framework of BootStrep, an FP6 project. The BioLexicon (BL) is a lexical resource designed for text mining in the bio-domain. It has been conceived to meet both domain requirements and upcoming ISO standards for lexical representation. The data model and data categories are compliant to the ISO Lexical Markup Framework and the Data Category Registry. The BioLexicon integrates features of lexicons and terminologies: term entries (and variants) derived from existing resources are enriched with linguistic features, including sub-categorization and predicate-argument information, extracted from texts. Thus, it is an extendable resource. Furthermore, the lexical entries will be aligned to concepts in the BioOntology, the ontological resource of the project. The BL implementation is an extensible relational database with automatic population procedures. Population relies on a dedicated input data structure allowing to upload terms and their linguistic properties and ?pull-and-push? them in the database. The BioLexicon teaches that the state-of-the-art is mature enough to aim at setting up a standard in this domain. Being conformant to lexical standards, the BioLexicon is interoperable and portable to other areas

A lexicon for biology and bioinformatics: the BOOTStrep experience

This paper describes the design, implementation and population of a lexical resource for biology and bioinformatics (the BioLexicon) developed within an ongoing European project. The aim of this project is text-based knowledge harvesting for support to information extraction and text mining in the biomedical domain. The BioLexicon is a large-scale lexical-terminological resource encoding different information types in one single integrated resource. In the design of the resource we follow the ISO/DIS 24613 ?Lexical Mark-up Framework? standard, which ensures reusability of the information encoded and easy exchange of both data and architecture. The design of the resource also takes into account the needs of our text mining partners who automatically extract syntactic and semantic information from texts and feed it to the lexicon. The present contribution first describes in detail the model of the BioLexicon along its three main layers: morphology, syntax and semantics; then, it briefly describes the database implementation of the model and the population strategy followed within the project, together with an example. The BioLexicon database in fact comes equipped with automatic uploading procedures based on a common exchange XML format, which guarantees that the lexicon can be properly populated with data coming from different sources

A LexO-Server Use Case: Languages and Cultures of Ancient Italy

Purpose: This paper presents a set of REST services called a LexO-server (https://github.com/andreabellandi/LexO-) for the management of lexical resources modeled as the OntoLex-Lemon model. This comes as a software backend, providing data access and manipulation to frontend developers, and will be exemplified through the Languages and Cultures of Ancient Italy CLARINIT related project. This is a use case where the creation and edition of an integrated system of LRs for ancient fragmentary languages will be shown in compliance with current digital humanities and Linked Open Data principles. Other relevant use cases will be mentioned for demonstrating the versatility of these services and how they can be easily integrated within more complex systems and/or interact with other independent back-ends

Lexically-based Ontologies and Ontologically Based Lexicons

This paper deals with the relations between ontologies and lexicons. We study the role of these two components and their evolution during the last years in the field of Computational Linguistics. Subsequently, we survey the current lines of research at ILC-CNR which tackle this topic. They involve (I) the reuse of already existing Lexical Resources to derive formal ontologies, (II) the conversion and combination of terminologies into rich and formal Lexical Resources and (III) the use of formal ontologies as the backbone of multilingual Lexical Resources

From Synsets to Videos: Enriching ItalWordNet Multimodally

Abstract The paper describes the multimodal enrichment of ItalWordNet action verbs' entries by means of an automatic mapping with a conceptual ontology of action types instantiated by video scenes (ImagAct). The two resources present significative differences as well as interesting complementary features, such that a mapping of these two resources can lead to a an enrichment of IWN, through the connection between synsets and videos apt to illustrate the meaning described by glosses. Here, we describe an approach inspired by ontology matching methods for the automatic mapping of ImagAct video scenes onto ItalWordNet. The experiments described in the paper are conducted on Italian, but the same methodology can be extended to other languages for which WordNets have been created, since ImagAct is available also for English, Chinese and Spanish. This source of multimodal information can be exploited to design second language learning tools, as well as for language grounding in action recognition in video sources and potentially for robotics