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 Q]: Our model yields the best results on both UAS and LAS metrics of all languages except the Japanese. As for Japanese, our model gives unsatisfactory results because the original treebank was written in Roman phonetic characters instead of hiragana, which is used by both common Japanese writing and our pre-trained embeddings. Despite this, our model overall still gives 1.0% higher average UAS and LAS than the previous best parser, BIAF. Although both BIAF and STACKPTR parsers have achieved relatively high parsing accuracies on the 12 languages and have all UAS higher than 90%, our model achieves state-of-the-art results in all languages for both UAS and LAS. Overall, our model reports more than 1.0% higher average UAS than STACKPTR and 0.3% higher than BIAF. 
 Question: What are performance compared to former models?
[EX A]: model overall still gives 1.0% higher average UAS and LAS than the previous best parser, BIAF our model reports more than 1.0% higher average UAS than STACKPTR and 0.3% higher than BIAF

[EX Q]: These sentiment scores were automatically obtained through the topic extraction and sentiment analysis pipeline introduced in our prior work BIBREF15 and pretrained on in-house psychiatric EHR text. 
 Question: How do they extract topics?
[EX A]:  automatically obtained through the topic extraction and sentiment analysis pipeline introduced in our prior work BIBREF15

[EX Q]: To evaluate the effectiveness of the proposed framework for the ATE task, we conduct experiments over four benchmark datasets from the SemEval ABSA challenge BIBREF1 , BIBREF18 , BIBREF12 . Table TABREF24 shows their statistics. INLINEFORM0 (SemEval 2014) contains reviews of the laptop domain and those of INLINEFORM1 (SemEval 2014), INLINEFORM2 (SemEval 2015) and INLINEFORM3 (SemEval 2016) are for the restaurant domain. In these datasets, aspect terms have been labeled by the task organizer. 
 Question: Which dataset(s) do they use to train the model?
[EX A]:
INLINEFORM0 (SemEval 2014) contains reviews of the laptop domain and those of INLINEFORM1 (SemEval 2014), INLINEFORM2 (SemEval 2015) and INLINEFORM3 (SemEval 2016) are for the restaurant domain.