Question answering models in closed domains

Discussed herein are devices, systems, and methods for determining an answer to a natural language question. A method can include receiving a question and a passage to be used to answer the question and executing (i) a first trained ML model, based on the passage and the question and in response to determining that the question, passage, or a combination thereof includes more than a first threshold number of out of vocabulary (OOV) words, relative to a general purpose language ML model, to generate a first answer to the question or (ii) executing a second trained ML model, based on the passage and the question and in response to determining the question, passage, or a combination thereof includes less than the first threshold number of out of vocabulary (OOV) words, relative to the general purpose language ML model, to generate a second answer to the question.