US 12518089 B2 / Jan 6, 2026

Machine learning for translation to structured computer readable representation

In general, the disclosure describes techniques for machine learning for translation to structured computer readable representation. An example method to generate a training set for a natural language translation model includes receiving, by a computing system, a grammar comprising rules, one or more of the rules being associated with random biases; generating, by the computing system, at least one of random trees or random graphs based on the random biases in the grammar; for each of the random trees or random graphs, by the computing system, generating a natural language sample; and generating, by the computing system, the training set with the random trees or random graphs and the corresponding natural language samples.