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Semantic Data Set Construction from Human Clustering and Spatial Arrangement ...
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Context vs Target Word: Quantifying Biases in Lexical Semantic Datasets ...
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AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ...
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AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ...
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Quantifying lexical usage: vocabulary pertaining to ecosystems and the environment
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Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ...
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Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ...
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Abstract:
We present the first evaluation of the applicability of a spatial arrangement method (SpAM) to a typologically diverse language sample, and its potential to produce semantic evaluation resources to support multilingual NLP, with a focus on verb semantics. We demonstrate SpAM’s utility in allowing for quick bottom-up creation of large-scale evaluation datasets that balance cross-lingual alignment with language specificity. Starting from a shared sample of 825 English verbs, translated into Chinese, Japanese, Finnish, Polish, and Italian, we apply a two-phase annotation process which produces (i) semantic verb classes and (ii) fine-grained similarity scores for nearly 130 thousand verb pairs. We use the two types of verb data to (a) examine cross-lingual similarities and variation, and (b) evaluate the capacity of static and contextualised representation models to accurately reflect verb semantics, contrasting the performance of large language-specific pretraining models with their multilingual equivalent on ...
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Keyword:
Computer and Information Science; Natural Language Processing; Neural Network
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URL: https://underline.io/lecture/6272-manual-clustering-and-spatial-arrangement-of-verbs-for-multilingual-evaluation-and-typology-analysis https://dx.doi.org/10.48448/2t2z-re45
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Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis
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Majewska, Olga; Vulic, Ivan; McCarthy, Diana. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.423, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020
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Investigating the cross-lingual translatability of VerbNet-style classification. ...
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Investigating the cross-lingual translatability of VerbNet-style classification.
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Word Sense Clustering and Clusterability
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In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01838502 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2016, 42, pp.245-275. ⟨10.1162/COLI⟩ (2016)
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Integrating character representations into Chinese word embedding
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Semantic clustering of pivot paraphrases
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In: International Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-01838559 ; International Conference on Language Resources and Evaluation, Jan 2014, Reykjavik, Iceland (2014)
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Quantifying lexical usage: vocabulary pertaining to ecosystems and the environment
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Finding Meaning in Context Using Graph Algorithms in Mono- and Cross-lingual Settings
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