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.

The best baseline model is NO-MOVE, reaching an accuracy of 30.3% on single sentences and 0.3 on complete paragraphs.
Question: How well did the baseline perform?
accuracy of 30.3% on single sentences and 0.3 on complete paragraphs

The dataset includes about 6,000 triples, comprised of videos, questions, and answer spans manually collected from screencast tutorial videos with spoken narratives for a photo-editing software.
Question: What kind of instructional videos are in the dataset?
tutorial videos for a photo-editing software

Methodology ::: Corpus-based Approach
Contextual information is informative in the sense that, in general, similar words tend to appear in the same contexts. In the corpus-based approach, we capture both of these characteristics and generate word embeddings specific to a domain. Methodology ::: Dictionary-based Approach
In Turkish, there do not exist well-established sentiment lexicons as in English. In this approach, we made use of the TDK (Turk Dil Kurumu - "Turkish Language Institution") dictionary to obtain word polarities.
Question: What word-based and dictionary-based feature are used?
generate word embeddings specific to a domain TDK (Turk Dil Kurumu - "Turkish Language Institution") dictionary to obtain word polarities