Decreasing lexical data sparsity in statistical syntactic parsing - experiments with named entities

In this paper we present preliminary experiments that aim to reduce lexical data sparsity in statistical parsing by exploiting information about named entities. Words in the WSJ corpus are mapped to named entity clusters and a latent variable constituency parser is trained and tested on the transformed corpus. We explore two different methods for mapping words to entities, and look at the effect of mapping various subsets of named entity types. Thus far, results show no improvement in parsing accuracy over the best baseline score; we identify possible problems and outline suggestions for future directions

Using distributional similarity to organise biomedical terminology

We investigate an application of distributional similarity techniques to the problem of structural organisation of biomedical terminology. Our application domain is the relatively small GENIA corpus. Using terms that have been accurately marked-up by hand within the corpus, we consider the problem of automatically determining semantic proximity. Terminological units are dened for our purposes as normalised classes of individual terms. Syntactic analysis of the corpus data is carried out using the Pro3Gres parser and provides the data required to calculate distributional similarity using a variety of dierent measures. Evaluation is performed against a hand-crafted gold standard for this domain in the form of the GENIA ontology. We show that distributional similarity can be used to predict semantic type with a good degree of accuracy

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)

D7.1. Criteria for evaluation of resources, technology and integration.

This deliverable defines how evaluation is carried out at each integration cycle in the PANACEA project. As PANACEA aims at producing large scale resources, evaluation becomes a critical and challenging issue. Critical because it is important to assess the quality of the results that should be delivered to users. Challenging because we prospect rather new areas, and through a technical platform: some new methodologies will have to be explored or old ones to be adapted

In search of knowledge: text mining dedicated to technical translation

Articolo pubblicato su CD e commercializzato direttamente dall'ASLIB (http://shop.emeraldinsight.com/product_info.htm/cPath/56_59/products_id/431). Programma del convegno su http://aslib.co.uk/conferences/tc_2011/programme.htm

Discovering multiword expressions

In this paper, we provide an overview of research on multiword expressions (MWEs), from a natural lan- guage processing perspective. We examine methods developed for modelling MWEs that capture some of their linguistic properties, discussing their use for MWE discovery and for idiomaticity detection. We con- centrate on their collocational and contextual preferences, along with their fixedness in terms of canonical forms and their lack of word-for-word translatatibility. We also discuss a sample of the MWE resources that have been used in intrinsic evaluation setups for these methods

Language resources for Italian: Towards the development of a corpus of annotated Italian multiword expressions

Napoli, Italy, December 5-7, 2016This paper describes the first resource annotated for multiword expressions (MWEs) in Italian. Two versions of this dataset have been prepared: the first with a fast markup list of out-of-context MWEs, and the second with an in-context annotation, where the MWEs are entered with their contexts. The paper also discusses annotation issues and reports the inter-annotator agreement for both types of annotations. Finally, the results of the first exploitation of the new resource, namely the automatic extraction of Italian MWEs, are presented

Collocations in Portuguese: A corpus-based approach to lexical patterns

Collocations and, more generally, multiword expressions, have been extensively studied for the English language and a large set of resources are available in terms of linguistic description and tools for language learning. On the contrary, combinatorial resources for Portuguese are scarce, although specific types of collocations, such as light verb constructions, nominal compounds and proverbs, have been the topic of many studies. This chapter reviews different theoretical perspectives on multiword expressions and collocations in Portuguese and presents in more detail the results of the COMBINA-PT project, a corpus-based approach to the study of collocations.info:eu-repo/semantics/publishedVersio

Language Resources for Italian: towards the Development of a Corpus of Annotated Italian Multiword Expressions

Questo contributo descrive la prima risorsa italiana annotatata con polirematiche. Sono state preparate due versioni del dataset: la prima con una lista di polirematiche senza contesto, e la seconda con annotazione in contesto. Il contributo discute le problematiche emerse durante l’annotazione e riporta il grado di accordo tra annotatori per entrambi i tipi di annotazione. Infine vengono presentati i risultati del primo impiego della nuova risorsa, ovvero l’estrazione automatica di polirematiche per l’italiano.This paper describes the first resource annotated for multiword expressions (MWEs) in Italian. Two versions of this dataset have been prepared: the first with a fast markup list of out-of-context MWEs, and the second with an in-context annotation, where the MWEs are entered with their contexts. The paper also discusses annotation issues and reports the inter-annotator agreement for both types of annotations. Finally, the results of the first exploitation of the new resource, namely the automatic extraction of Italian MWEs, are presented

Multi-Word Expressions in spoken language: PoliSdict

The term multiword expressions (MWEs) is referred-to a group of words with a unitary meaning, not inferred from that of the words that compose it, both in current use and in technical-specialized languages. In this paper, we describe PoliSdict an Italian electronic dictionary composed of multi-word expressions (MWEs) automatically extracted from a multimodal corpus grounded on political speech language, currently being developed at the "Maurice Gross" Laboratory of the Department of Political Sciences, Social and Communication of the University of Salerno, thanks to a loan from the company Network Contacts. We introduce the methodology of creation and the first results of a systematic analysis which considered terminological labels, frequency labels, recurring syntactic patterns, further proposing an associated ontology.Con il termine polirematica si fa generalmente riferimento ad un gruppo di parole con significato unitario, non desumibile da quello delle parole che lo compongono, sia nell’uso corrente sia in linguaggi tecnico-specialistici. In questo contributo viene presentato PoliSdict un dizionario elettronico in lingua italiana composto da espressioni polirematiche occorrenti nel parlato spontaneo estratte a partire da un corpus multimodale di dominio politico in lingua italiana in corso di ampliamento presso il Laboratorio “Maurice Gross” del Dipartimento di Scienze Politiche, Sociali e della Comunicazione dell’Università degli Studi di Salerno, grazie a un finanziamento della società Network Contacts. Viene presentata la metodologia di creazione ed i primi risultati di un'analisi sistematica che ha considerato etichette terminologiche, marche d'uso e pattern ricorrenti, proponendo infine un’ontologia associata