Intermediate · Evaluation
Choice of Plausible Alternatives (COPA)
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A dataset and evaluation task designed to test an LLM's ability to choose the more plausible cause or consequence for a given premise.
Technical Definition
A dataset and evaluation task designed to test an LLM's ability to choose the more plausible cause or consequence for a given premise.
How it works
Choice of Plausible Alternatives (COPA) is a benchmark dataset used to evaluate commonsense reasoning in language models. It presents a premise and asks the model to choose the more likely cause or effect from two alternatives. This task effectively measures an LLM's understanding of cause-and-effect relationships and general world knowledge.
Related Concepts
- Commonsense reasoning — AI's attempt to replicate the human ability to make educated guesses about ordinary, everyday situations.
- Natural Language Understanding (NLU) — The ability of a computer program to understand human language as it is spoken or written.