Valeria Quochi

The BioLexicon: A large-scale terminological resource for biomedical text mining

BackgroundDue to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events.ResultsThis article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard.ConclusionsThe BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring.

The language resource Strategic Agenda: the FLaReNet synthesis of community recommendations

Abstract The main purpose of this paper is to serve as a landmark for future research and in particular for future strategic, infrastructural and coordination initiatives. It presents a preliminary plan for actions and infrastructures that could become the basis for future initiatives in the sector of Language Resources and Technologies (LRTs). The FLaReNet Language Resource Strategic Agenda presents a set of recommendations for the development and progress of LRT in Europe, as issued from a three-year consultation of the FLaReNet European project. Recommendations cover a broad range of topics and activities, spanning over production and use of language resources, licensing, maintenance and preservation issues, infrastructures for language resources, resource identification and sharing, evaluation and validation, interoperability and policy issues. The intended recipients belong to a large set of players and stakeholders in LRT, ranging from individuals to research and education institutions, to policy-makers, funding agencies, SMEs and large companies, service and media providers. The main goal of these recommendations is to serve as an instrument to support stakeholders in planning for and addressing the urgencies of the LRT of the future.

Lexicons, Terminologies, Ontologies: Reflections from Experiences in Resource Construction

This contribution, aims at highlighting the strong interconnection between lexicons, terminologies and ontologies and especially the fundamental role that ontologies and lexica mutually play. Our view is that lexical resources are evolving in nature, from ontologically based lexicons we are going towards lexically based ontologies. We explore different instantiations of the current trend of using formal ontologies as a core module of computational lexicons, presenting the advantages especially in multilingual and terminological contexts. We present work showing that the lexical knowledge already present in non formal computational lexicons can be exploited to derive or enrich a formal ontology without much manual effort. In the terminology domain, we describe the construction of a resource for biology, directly linked to a parallel domain-ontology, that combines characteristics of both lexicons and terminologies, so that is can allow for intelligent access to content. Finally, we describe our experience in two projects in which formal ontologies play a central role in the context of multilingual computational lexicons, where the ontology is what acts as the glue among the different monolingual lexicons and what provides cross-lingual reasoning capabilities.

A Standard Lexical-Terminological Resource for the Bio Domain

The present paper describes a large-scale lexical resource for the biology domain designed both for human and for machine use. This lexicon aims at semantic interoperability and extendability, through the adoption of ISO-LMF standard for lexical representation and through a granular and distributed encoding of relevant information. The first part of this contribution focuses on three aspects of the model that are of particular interest to the biology community: the treatment of term variants, the representation on bio events and the alignment with a domain ontology. The second part of the paper describes the physical implementation of the model: a relational database equipped with a set of automatic uploading procedures. Peculiarity of the BioLexicon is that it combines features of both terminologies and lexicons. A set verbs relevant for the domain is also represented with full details on their syntactic and semantic argument structure.

Inferring the Semantics of Temporal Prepositions in Italian

In this work we report on the results of a preliminary corpus study of Italian on the semantics of temporal prepositions, which is part of a wider project on the automatic recognition of temporal relations. The corpus data collected supports our hypothesis that each temporal preposition can be associated with one prototypical temporal relation, and that deviations from the prototype can be explained as determined by the occurrence of different semantic patterns. The motivation behind this approach is to improve methods for temporal annotation of texts for content based access to information. The corpus study described in this paper led to the development of a preliminary set of heuristics for automatic annotation of temporal relations in text/discourse.