Dawn Knight


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Leveraging Pre-Trained Embeddings for Welsh Taggers
Ignatius Ezeani | Scott Piao | Steven Neale | Paul Rayson | Dawn Knight
Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)

While the application of word embedding models to downstream Natural Language Processing (NLP) tasks has been shown to be successful, the benefits for low-resource languages is somewhat limited due to lack of adequate data for training the models. However, NLP research efforts for low-resource languages have focused on constantly seeking ways to harness pre-trained models to improve the performance of NLP systems built to process these languages without the need to re-invent the wheel. One such language is Welsh and therefore, in this paper, we present the results of our experiments on learning a simple multi-task neural network model for part-of-speech and semantic tagging for Welsh using a pre-trained embedding model from FastText. Our model’s performance was compared with those of the existing rule-based stand-alone taggers for part-of-speech and semantic taggers. Despite its simplicity and capacity to perform both tasks simultaneously, our tagger compared very well with the existing taggers.

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Unsupervised multi-word term recognition in Welsh
Irena Spasić | David Owen | Dawn Knight | Andreas Artemiou
Proceedings of the Celtic Language Technology Workshop


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Towards a Welsh Semantic Annotation System
Scott Piao | Paul Rayson | Dawn Knight | Gareth Watkins
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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Leveraging Lexical Resources and Constraint Grammar for Rule-Based Part-of-Speech Tagging in Welsh
Steven Neale | Kevin Donnelly | Gareth Watkins | Dawn Knight
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


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Lexical Coverage Evaluation of Large-scale Multilingual Semantic Lexicons for Twelve Languages
Scott Piao | Paul Rayson | Dawn Archer | Francesca Bianchi | Carmen Dayrell | Mahmoud El-Haj | Ricardo-María Jiménez | Dawn Knight | Michal Křen | Laura Löfberg | Rao Muhammad Adeel Nawab | Jawad Shafi | Phoey Lee Teh | Olga Mudraya
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The last two decades have seen the development of various semantic lexical resources such as WordNet (Miller, 1995) and the USAS semantic lexicon (Rayson et al., 2004), which have played an important role in the areas of natural language processing and corpus-based studies. Recently, increasing efforts have been devoted to extending the semantic frameworks of existing lexical knowledge resources to cover more languages, such as EuroWordNet and Global WordNet. In this paper, we report on the construction of large-scale multilingual semantic lexicons for twelve languages, which employ the unified Lancaster semantic taxonomy and provide a multilingual lexical knowledge base for the automatic UCREL semantic annotation system (USAS). Our work contributes towards the goal of constructing larger-scale and higher-quality multilingual semantic lexical resources and developing corpus annotation tools based on them. Lexical coverage is an important factor concerning the quality of the lexicons and the performance of the corpus annotation tools, and in this experiment we focus on evaluating the lexical coverage achieved by the multilingual lexicons and semantic annotation tools based on them. Our evaluation shows that some semantic lexicons such as those for Finnish and Italian have achieved lexical coverage of over 90% while others need further expansion.


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Introducing DRS (The Digital Replay System): a Tool for the Future of Corpus Linguistic Research and Analysis
Dawn Knight | Paul Tennent
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

This paper outlines the new resource technologies, products and applications that have been constructed during the development of a multi-modal (MM hereafter) corpus tool on the DReSS project (Understanding New Forms of the Digital Record for e-Social Science), based at the University of Nottingham, England. The paper provides a brief outline of the DRS (Digital Replay System, the software tool at the heart of the corpus), highlighting its facility to display synchronised video, audio and textual data and, most relevantly, a concordance tool capable of interrogating data constructed from textual transcriptions anchored to video or audio, and from coded annotations of specific features of gesture-in-talk. This is complemented by a real-time demonstration of the DRS interface in-use as part of the LREC 2008 conference. This will serve to show the manner in which a system such as the DRS can be used to facilitate the assembly, storage and analysis of multi modal corpora, supporting both qualitative and quantitative approaches to the analysis of collected data.