0000000000255996
AUTHOR
Pierre Zweigenbaum
Overviewing Important Aspects of the Last Twenty Years of Research in Comparable Corpora
The beginning of the 1990s marked a radical turn in various NLP applications towards using large collections of texts.
Overview of the Second BUCC Shared Task: Spotting Parallel Sentences in Comparable Corpora
This paper presents the BUCC 2017 shared task on parallel sentence extraction from comparable corpora. It recalls the design of the datasets, presents their final construction and statistics and the methods used to evaluate system results. 13 runs were submitted to the shared task by 4 teams, covering three of the four proposed language pairs: French-English (7 runs), German-English (3 runs), and Chinese-English (3 runs). The best F-scores as measured against the gold standard were 0.84 (German-English), 0.80 (French-English), and 0.43 (Chinese-English). Because of the design of the dataset, in which not all gold parallel sentence pairs are known, these are only minimum values. We examined …
BUCC Shared Task: Cross-Language Document Similarity
We summarise the organisation and results of the first shared task aimed at detecting the most similar texts in a large multilingual collection. The dataset of the shared was based on Wikipedia dumps with interlanguage links with further filtering to ensure comparability of the paired articles. The eleven system runs we received have been evaluated using the TREC evaluation metrics. 1 Task description Parallel corpora of original texts with their translations provide the basis for multilingual NLP applications since the beginning of the 1990s. Relative scarcity of such resources led to greater attention to comparable (=less parallel) resources to mine information about possible translations…