instruction:
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:
Maximum Entropy theory is applied to solve Vietnamese word segmentation BIBREF15 , BIBREF22 , BIBREF23 . There are several studies about the Vietnamese word segmentation task over the last decade. Dinh et al. started this task with Weighted Finite State Transducer (WFST) approach and Neural Network approach BIBREF9 . In addition, machine learning approaches are studied and widely applied to natural language processing and word segmentation as well. In fact, several studies used support vector machines (SVM) and conditional random fields (CRF) for the word segmentation task BIBREF7 , BIBREF8 . 
 Question: Which approaches have been applied to solve word segmentation in Vietnamese?
answer:
Maximum Entropy Weighted Finite State Transducer (WFST)  support vector machines (SVM) conditional random fields (CRF)


question:
Compared to the in-context-parsing-based system, the combination with exact string matching yields a gain in recall of over 6%, and the combination with inflectional string matching yields an even bigger gain of almost 8%, at precision losses of 0.6% and 0.8%, respectively. 
 Question: What compleentary PIE extraction methods are used to increase reliability further?
answer:
exact string matching inflectional string matching


question:
To ensure the universality and general applicability of the curriculum, we perform an in-depth investigation on three publicly available conversation corpora, PersonaChat BIBREF12, DailyDialog BIBREF13 and OpenSubtitles BIBREF7, consisting of 140 248, 66 594 and 358 668 real-life conversation samples, respectively. 
 Question: What three publicly available coropora are used?
answer:

PersonaChat BIBREF12 DailyDialog BIBREF13 OpenSubtitles BIBREF7