Reproduction, replication, analysis and adaptation of a term alignment approach

Author:

Repar AndražORCID,Martinc MatejORCID,Pollak SenjaORCID

Abstract

AbstractIn this paper, we look at the issue of reproducibility and replicability in bilingual terminology alignment (BTA). We propose a set of best practices for reproducibility and replicability of NLP papers and analyze several influential BTA papers from this perspective. Next, we present our attempts at replication and reproduction, where we focus on a bilingual terminology alignment approach described by Aker et al. (Extracting bilingual terminologies from comparable corpora. In: Proceedings of the 51st annual meeting of the association for computational linguistics, vol. 1 402–411, 2013) who treat bilingual term alignment as a binary classification problem and train an SVM classifier on various dictionary and cognate-based features. Despite closely following the original paper with only minor deviations—in areas where the original description is not clear enough—we obtained significantly worse results than the authors of the original paper. We then analyze the reasons for the discrepancy and describe our attempts at adaptation of the approach to improve the results. Only after several adaptations, we achieve results which are close to the results published in the original paper. Finally, we perform the experiments to verify the replicability and reproducibility of our own code. We publish our code and datasets online to assure the reproducibility of the results of our experiments and implement the selected BTA models in an online platform making them easily reusable even by the technically less-skilled researchers.

Funder

Javna Agencija za Raziskovalno Dejavnost RS

Horizon 2020

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Linguistics and Language,Education,Language and Linguistics

Reference56 articles.

1. Aker, A., Paramita, M., & Gaizauskas, R. (2013). Extracting bilingual terminologies from comparable corpora. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: Vol. 1. Long Papers (pp 402–411).

2. Aker, A., Paramita, M. L., Pinnis, M., & Gaizauskas, R. (2014). Bilingual dictionaries for all EU languages. In Proceedings of 9th International Conference on Language Resources and Evaluation. (pp 2839–2845).

3. Arčan, M., Turchi, M., Tonelli, S., & Buitelaar, P. (2014). Enhancing statistical machine translation with bilingual terminology in a CAT environment. https://doi.org/10.13140/2.1.1019.8404.

4. Bader, B. W., & Chew. P. A. (2008). Enhancing multilingual latent semantic analysis with term alignment information. In Proceedings of the 22nd International Conference on Computational Linguistics: Vol. 1. Association for Computational Linguistics (pp 49–56).

5. Baisa, V., Ulipová, B., & Cukr, M. (2015). Bilingual terminology extraction in Sketch Engine. In 9th Workshop on Recent Advances in Slavonic Natural Language Processing. (pp 61–67).

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