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:
We evaluate our newly proposed models and related baselines in several low-resource settings across different languages with real, distantly supervised data with non-synthetic noise. The advanced modeling of the noisy labels substantially improves the performance up to 36% over methods without noise-handling and up to 9% over all other noise-handling baselines. 
 Question: Did they evaluate against baseline?

Ex Output:
Yes


Ex Input:
The test-set accuracies obtained by different learning methods, including the current state-of-the-art results, are presented in Table TABREF11 . 
 Question: what models did they compare to?

Ex Output:
High-order CNN, Tree-LSTM, DRNN, DCNN, CNN-MC, NBoW and SVM 


Ex Input:
Prior to the SAOKE data set, an annotated data set for OIE tasks with 3,200 sentences in 2 domains was released in BIBREF20 to evaluate OIE algorithms, in which the data set was said BIBREF20 “13 times larger than the previous largest annotated Open IE corpus”. 
 Question: What's the size of the previous largest OpenIE dataset?

Ex Output:

3,200 sentences


