1) NAME_1 and Understand the Document: This step is crucial as it forms the foundation for generating meaningful queries. Without a thorough understanding of the document's content, it would be challenging to formulate relevant questions.

2) Identify Important Concepts and Keywords: Identifying key concepts and keywords helps you focus on the most crucial aspects of the document. These elements often serve as the basis for generating insightful queries.

3) Formulate Open-Ended Questions: Open-ended questions encourage detailed and informative responses. By formulating such questions, you can gather more comprehensive information and insights from the document.
Taking into account these three steps, please generate the queries for the text in the triple quotas.
"""The training data sets for task a contain annotated articles from PubMed, where annotated means that MeSH terms have been assigned to the articles by the human curators in PubMed. Table 1 provides information about the provided datasets. Note that the main difference between those datasets among the different years, apart from the size, is the MeSH terms used. For example the 2015 training datasets contain articles where MeSH 2015 have been assigned. Also, for 2014, 2015 and 2016 there are two versions of the training data available. The small version (wrt size) consists of articles that belong to the pool of journals that the BioASQ team used to select the articles for the test data (this was a subset of the available journals). The bigger version consists of articles from every available journal. Since 2017 articles for the test data will be selected from all available journals, so only one corresponding training data set will be available. The evaluation of the results during each year of the challenge is performed using the corresponding version of the MeSH terms, thus their usage is highly recommended. The training datasets of previous years of the challenge are also available for reference reasons. Note that not every MeSH term is covered in the datasets. Participants, are allowed to use unlimited resources to train their systems.""".
Let's do it step by step. 
The output should be a JSON object with keys the proposed steps to solve the problem.