Automatic Spanish Translation of the SQuAD Dataset for Multilingual Question Answering
Table 2: Number of (ces,qes,aes) examples in the final SQuAD-es v1.1 Datasets over the total number of the original SQuAD v.1.1 (cen,qen,qen). We also computed the average length for the context, question and answers in terms of tokens.
['[EMPTY]', '[BOLD] SQuAD-es', '[BOLD] SQuAD-es-small']
After the translation, we applied some heuristics to clean and refine the retrieved (ces,qes,aes) examples. Based on the error analysis, we post-processed the type II errors. In particular, we first filter out words in the answers translations belonging to the next sentences. Then, we removed the extra leading and trailing punctuation. Eventually, we also removed empty answers translations that might be generated during the translation process. Moreover, in order to examine the impact on the QA system performance, we produced two versions of the SQuAD-es v1.1 training dataset. A standard one, containing all the translated (ces,qes,aes) examples and referred to as SQuAD-es v1.1 and another that keep only the (ces,qes,aes) examples retrieved without the use of the alignment, named SQuAD-es-small. We also show the average context, question and answer length in terms of token. As a result, we the SQuAD-es v1.1 training contains almost the 100% of the SQuAD v1.1 data while the SQuAD-es-small v1.1 is approximately half the size, with a about 53% of the data. In the next section, these two SQUAD-es v1.1 datasets will be employed to train Spanish question Answering models.