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Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification
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In: Front Artif Intell (2022)
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English WordNet Taxonomic Random Walk Pseudo-Corpora
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In: Conference papers (2020)
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Language related issues for machine translation between closely related south Slavic languages
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Synthetic, Yet Natural: Properties of WordNet Random Walk Corpora and the impact of rare words on embedding performance
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In: Conference papers (2019)
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Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings
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In: Articles (2019)
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| 8 |
Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian ...
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Is it worth it? Budget-related evaluation metrics for model selection ...
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Abstract:
Creating a linguistic resource is often done by using a machine learning model that filters the content that goes through to a human annotator, before going into the final resource. However, budgets are often limited, and the amount of available data exceeds the amount of affordable annotation. In order to optimize the benefit from the invested human work, we argue that deciding on which model one should employ depends not only on generalized evaluation metrics such as F-score, but also on the gain metric. Because the model with the highest F-score may not necessarily have the best sequencing of predicted classes, this may lead to wasting funds on annotating false positives, yielding zero improvement of the linguistic resource. We exemplify our point with a case study, using real data from a task of building a verb-noun idiom dictionary. We show that, given the choice of three systems with varying F-scores, the system with the highest F-score does not yield the highest profits. In other words, in our case ... : 7 pages, 1 figure, 5 tables, In proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1807.06998
https://dx.doi.org/10.48550/arxiv.1807.06998
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| 10 |
Quantitative Fine-grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian
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In: Articles (2018)
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| 11 |
Is it worth it? Budget-related evaluation metrics for model selection
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In: Conference papers (2018)
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hr500k – A Reference Training Corpus of Croatian.
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In: Conference papers (2018)
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Fine-grained human evaluation of neural versus phrase-based machine translation ...
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| 18 |
Fine-Grained Human Evaluation of Neural Versus Phrase-Based Machine Translation
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In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 121-132 (2017) (2017)
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