1. There is the Yahoo QA dataset that might be helpful. Also you can crawl specific websites for such questions 2. semi-manually come up with templates (a gram

1. There is the Yahoo QA dataset that might be helpful. Also you can crawl specific websites for such questions 2. semi-manually come up with templates (a grammar for the questions). You have to analyse the dataset in a unsupervised way to find out the common patterns and sanatize the results. 3. maybe step 2 is enough. 4. markov networks are useful in this context but I can be wrong > A template should be translatable to a bunch of queries (e.g.: GraphQL format). Not the hard part I believe. Yes once you have the templates with typed variables (named entities, adjectives, etc...) like you describe you can write the code to search for the results. I doubt GraphQL is a good solution for that problem. You can't translate the templates into a search on the fly. It's a mapping that you need to build manually or automatically. I think in your case SQL will be fine. Have a look at https://github.com/machinalis/quepy https://github.com/machinalis/quepy