Creating language resources for under-resourced languages: methodologies, and experiments with Arabic

Language resources are important for those working on computational methods to analyse and study languages. These resources are needed to help advancing the research in fields such as natural language processing, machine learning, information retrieval and text analysis in general. We describe the creation of useful resources for languages that currently lack them, taking resources for Arabic summarisation as a case study. We illustrate three different paradigms for creating language resources, namely: (1) using crowdsourcing to produce a small resource rapidly and relatively cheaply; (2) translating an existing gold-standard dataset, which is relatively easy but potentially of lower quality; and (3) using manual effort with appropriately skilled human participants to create a resource that is more expensive but of high quality. The last of these was used as a test collection for TAC-2011. An evaluation of the resources is also presented. The current paper describes and extends the resource creation activities and evaluations that underpinned experiments and findings that have previously appeared as an LREC workshop paper (El-Haj et al 2010), a student conference paper (El-Haj et al 2011b), and a description of a multilingual summarisation pilot (El-Haj et al 2011c; Giannakopoulos et al 2011). M. El-Haj School of Computing and Communications, Lancaster University, UK Tel.: +44(0)1524 51 0348 E-mail: [email protected] U. Kruschwitz CSEE, University of Essex, UK Tel.: +44 (0)1206 87 2669 E-mail: [email protected] C. Fox CSEE, University of Essex, UK Tel.: +44 (0)1206 87 2576 E-mail: [email protected] 2 El-Haj, Kruschwitz and Fox