In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

Ex Input:
Although techniques for constructing this knowledge base are outside the scope of this paper, we briefly mention them. Tables were constructed using a mixture of manual and semi-automatic techniques
Question: How is the semi-structured knowledge base created?

Ex Output:
using a mixture of manual and semi-automatic techniques

Ex Input:
To be able to employ the trained model, test sets are first translated to English via machine translation and then inference takes place. For machine translation, Google translation API is used.
Question: how did the authors translate the reviews to other languages?

Ex Output:
Using Google translation API.

Ex Input:
We used the annotated dataset reported by degen2015investigating, a dataset of the utterances from the Switchboard corpus of telephone dialogues BIBREF21 that contain the word some. The dataset consists of 1,362 unique utterances with a noun phrase containing some (some-NP). For each example with a some-NP, degen2015investigating collected inference strength ratings from at least 10 participants recruited on Amazon's Mechanical Turk. Participants saw both the target utterance and ten utterances from the preceding discourse context. They then rated the similarity between the original utterance like (UNKREF8) and an utterance in which some was replaced with some, but not all like (UNKREF9), on a 7-point Likert scale with endpoints labeled "very different meaning" (1) and "same meaning" (7). Low similarity ratings thus indicate low inference strength, and high similarity ratings indicate high inference strength.
Question: Which dataset do they use?

Ex Output:
the annotated dataset reported by degen2015investigating, a dataset of the utterances from the Switchboard corpus of telephone dialogues BIBREF21 that contain the word some