MLQA: Evaluating Cross-lingual Extractive Question Answering
Table 10: Number of mined parallel sentences as a function of how many languages the sentences are parallel between
['[BOLD] N-way', '[BOLD] en', '[BOLD] de', '[BOLD] es', '[BOLD] ar', '[BOLD] zh', '[BOLD] vi', '[BOLD] hi']
As the number of languages that a parallel sentence is shared between increases, the number of such sentences decreases. When we look for 7-way aligned examples, we only find 1340 sentences from the entirety of the 7 Wikipedia. Additionally, most of these sentences are the first sentence of the article, or are uninteresting. However, if we choose 4-way parallel sentences, there are plenty of sentences to choose from. We sample evenly from each combination of English and 3 of the 6 target languages. This ensures that we have an even distribution over all the target languages, as well as ensuring we have even numbers of instances that will be parallel between target language combinations.