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Textual Variations Affect Human Judgements of Sentiment Values
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CorCenCC: Corpws Cenedlaethol Cymraeg Cyfoes – the National Corpus of Contemporary Welsh ...
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Metaphorical Expressions in Automatic Arabic Sentiment Analysis
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Infrastructure for Semantic Annotation in the Genomics Domain
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Open Welsh Language Resources for a Corpus Annotation Framework
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Leveraging Pre-Trained Embeddings for Welsh Taggers
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Abstract:
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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URL: https://eprints.lancs.ac.uk/id/eprint/135950/
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Profiling Medical Journal Articles Using a Gene Ontology Semantic Tagger
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Creating and validating multilingual semantic representations for six languages:expert versus non-expert crowds
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Towards a Welsh semantic tagger:creating lexicons for a resource poor language
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A time-sensitive historical thesaurus-based semantic tagger for deep semantic annotation
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A time-sensitive historical thesaurus-based semantic tagger for deep semantic annotation
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Lexical Coverage Evaluation of Large-scale Multilingual Semantic Lexicons ...
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Lexical coverage evaluation of large-scale multilingual semantic lexicons for twelve languages
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Lexical coverage evaluation of large-scale multilingual semantic lexicons for twelve languages
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