Confident match Ambiguous tie Unfilled required slot

Function-Call Argument Grounding Simulator (2D)

Before an LLM agent can invoke a real function, every argument it proposes has to be grounded: a span of the user's own words has to be matched to the right typed parameter of the function's schema. This 2D engine performs that grounding for real — it tokenizes the utterance, extracts typed candidate spans (numbers, dates, quoted strings, enum vocabulary, capitalized names), scores every span against every schema slot with a genuine type-compatibility and string-similarity formula, then greedily assigns the highest-scoring free pairs. Ambiguous near-ties and unfilled required slots are flagged live, and typing a new sentence recomputes the whole assignment from scratch.