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.
--------
Question: We evaluate our model on both English and Chinese segmentation. For both languages we used standard datasets for word segmentation and language modeling. English
The Brent corpus is a standard corpus used in statistical modeling of child language acquisition BIBREF15 , BIBREF16  We use the commonly used version of the PTB prepared by BIBREF17 Since Chinese orthography does not mark spaces between words, there have been a number of efforts to annotate word boundaries. We evaluate against two corpora that have been manually segmented according different segmentation standards. The Beijing University Corpus was one of the corpora used for the International Chinese Word Segmentation Bakeoff BIBREF18 . We use the Penn Chinese Treebank Version 5.1 BIBREF19 . 
 Question: What dataset is used?

Answer: Brent corpus PTB  Beijing University Corpus Penn Chinese Treebank


Question: After Korektor, there are 4262 unique sentences (including 150 seed sentences) that form the COSTRA 1.0 dataset. 
 Question: How many sentence transformations on average are available per unique sentence in dataset?

Answer: 27.41 transformation on average of single seed sentence is available in dataset.


Question: We end up with two salient roles called Anchors and Punctual speakers:

the Anchor speakers (A) are above the threshold of 1% for both criteria, meaning they are intervening often and for a long time thus holding an important place in interaction;

the Punctual speakers (PS) on the contrary are below the threshold of 1% for both the total number of turns and the total speech time. 
 Question: How many categories do authors define for speaker role?

Answer:
 two salient roles called Anchors and Punctual speakers


