I have read the documentation but it is not clear. Please give a simple example
Training data quality standards The file must contain at least 49 unique questions. The number of records must be at least 50 times the number of fields that are identified in your Solr configuration. For example, if your collection defines five fields, you must have at least 250 records in your training data. At least two different relevance labels must exist in the data and those labels must be well represented. A label is well represented if it occurs at least once for every 100 unique questions. For example, you have 300 unique questions and you use a relevance scale of 1,2,3,4. At least two distinct labels (for example, 1 and 4) must each appear three times (0.01 X 300) in the training data. Do not use zero (0) in your relevance scale
Have you tried the Cranfield example described here? https://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/doc/retrieve-rank/get_start.shtml#create-collection It provides sample data to index and corresponding training data to train a ranker with. You can model your training data after this example.
Rank and Retrieve - data format quetion 0 Answers
Retrieve & Rank relevance label 0 1 Answer