Definition: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Input: On another note, we apply our formalization to evaluate multilingual $ extsc {bert} $'s syntax knowledge on a set of six typologically diverse languages. Although it does encode a large amount of information about syntax (more than $81\%$ in all languages), it only encodes at most $5\%$ more information than some trivial baseline knowledge (a type-level representation). This indicates that the task of POS labeling (word-level POS tagging) is not an ideal task for contemplating the syntactic understanding of contextual word embeddings. We see thatin all analysed languagestype level embeddings can already capture most of the uncertainty in POS tagging. We also see that BERT only shares a small amount of extra information with the task, having small (or even negative) gains in all languages. Finally, when put into perspective, multilingual $ extsc {bert} $'s representations do not seem to encode much more information about syntax than a trivial baseline. $ extsc {bert} $ only improves upon fastText in three of the six analysed languagesand even in those, it encodes at most (in English) $5\%$ additional information.
Output:
Was any variation in results observed based on language typology?