instruction:
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.
question:
In this section, we present the experimental setting for this task

Corpus: SEAME (South East Asia Mandarin-English), a conversational Mandarin-English code-switching speech corpus consists of spontaneously spoken interviews and conversations BIBREF8 .
answer:
What languages are explored in the work?

question:
We extract data from the WMT'14 English-French (En-Fr) and English-German (En-De) datasets. To create a larger discrepancy between the tasks, so that there is a clear dataset size imbalance, the En-De data is artificially restricted to only 1 million parallel sentences, while the full En-Fr dataset, comprising almost 40 million parallel sentences, is used entirely.
answer:
What datasets are used for experiments?

question:
These models define parametrized similarity scoring functions $: Q imes T
ightarrow \mathbb {R}$ , where $Q$ is the set of natural language questions and $T$ is the set of paraphrases of logical forms.
answer:
Does a neural scoring function take both the question and the logical form as inputs?