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.

Q: Based on annotated corpora and token-based features, studies used machine learning approaches to build word segmentation systems with accuracy about 94%-97%. 
 Question: How successful are the approaches used to solve word segmentation in Vietnamese?

A: Their accuracy in word segmentation is about 94%-97%.
****
Q: The experimental results are shown in Table 1, where it can be seen that autoencoders outperformed MLP and CNN outperformed autoencoders with the highest achieved accuracy of 82.6%. 
 Question: What was their performance on the dataset?

A: accuracy of 82.6%
****
Q: The input document/summary that may have unordered sentences is processed so that it will have sentences clustered together. To test our approach, we jumble the ordering of sentences in a document, process the unordered document and compare the similarity of the output document with the original document. To structure an unordered document is an essential task in many applications. It is a post-requisite for applications like multiple document extractive text summarization where we have to present a summary of multiple documents. It is a prerequisite for applications like question answering from multiple documents where we have to present an answer by processing multiple documents. 
 Question: What is an unordered text document, do these arise in real-world corpora?

A:
A unordered text document is one where sentences in the document are disordered or jumbled. It doesn't appear that unordered text documents appear in corpora, but rather are introduced as part of processing pipeline.
****