Symbol P
P is part of the quantity the equation computes from the expression on the right.
Read this term in its guide →Published equation contexts
Because retrieval and generation are separable, an end-to-end score is nearly uninformative about which one broke. Decompose it. Let be the retrieved set and S(x) the set of spans that would suffice to answer x : . The first factor is a pure retrieval quantity: recall at k , measurable against relevance judgements with no generator involved, using the established information-retrieval apparatus that BEIR standardised [ 6 ] . The second is a pure generation quantity: given that sufficient evidence was present, did the model use it faithfully? Es and colleagues built RAGAS to score exactly this separation — retrieval effectiveness, the faithfulness with…
P is part of the quantity the equation computes from the expression on the right.
Read this term in its guide →is one factor in the product that computes the quantity on the left.
Read this term in its guide →x is one factor in the product that computes the quantity on the left.
Read this term in its guide →S is one factor in the product that computes the quantity on the left.
Read this term in its guide →Read it with the definitions, units, and assumptions supplied by the article.
A symbol can carry a different meaning in another article. Each occurrence keeps its own guide and term definitions.
Equation 20 · AI Agents & Systems
This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.
Because retrieval and generation are separable, an end-to-end score is nearly uninformative about which one broke. Decompose it. Let be the retrieved set and S(x) the set of spans that would suffice to answer x : . The first factor is a pure retrieval quantity: recall at k , measurable against relevance judgements with no generator involved, using the established information-retrieval apparatus that BEIR standardised [ 6 ] . The second is a pure generation quantity: given that sufficient evidence was present, did the model use it faithfully? Es and colleagues built RAGAS to score exactly this separation — retrieval effectiveness, the faithfulness with…
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