mlsanityData to 14 Oct 2026

ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus

arXiv 2107.06632 ↗First posted 14 Jul 2021cs.CLcited by 3

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Abstract (arXiv)

With more than 7000 languages worldwide, multilingual natural language processing (NLP) is essential both from an academic and commercial perspective. Researching typological properties of languages is fundamental for progress in multilingual NLP. Examples include assessing language similarity for effective transfer learning, injecting inductive biases into machine learning models or creating resources such as dictionaries and inflection tables. We provide ParCourE, an online tool that allows to browse a word-aligned parallel corpus, covering 1334 languages. We give evidence that this is useful for typological research. ParCourE can be set up for any parallel corpus and can thus be used for typological research on other corpora as well as for exploring their quality and properties.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 10 of its 43 references that are in the map. First posted on arXiv 14 Jul 2021.

Builds on

10 of 43 references.

References · 10

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2021Word Alignment by Fine-tuning Embeddings on Parallel Corporacited by 186
  3. 2020SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddingscited by 156
  4. 2019Jointly Learning to Align and Translate with Transformer Modelscited by 75
  5. 2016Zero-Resource Translation with Multi-Lingual Neural Machine Translationcited by 46
  6. 2016Multi-Source Neural Translationcited by 37
  7. 2017Attention Strategies for Multi-Source Sequence-to-Sequence Learningcited by 32
  8. 2020End-to-End Neural Word Alignment Outperforms GIZA++cited by 28
  9. 2017Past, Present, Future: A Computational Investigation of the Typology of Tense in 1000 Languagescited by 13
  10. 2018Emerging Language Spaces Learned From Massively Multilingual Corporacited by 9

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Cited by year

Citing papers per year: 2021: 1; 2022: 2.

3 papers.

  1. 2021Graph Algorithms for Multiparallel Word Alignmentcited by 4
  2. 2022Graph Neural Networks for Multiparallel Word Alignmentcited by 4
  3. 2022Graph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Taggingcited by 4