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fix: minor typo in context_precision.md #2050

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fix: minor typo in context_precision.md #2050

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6 changes: 3 additions & 3 deletions docs/concepts/metrics/available_metrics/context_precision.md
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Expand Up @@ -17,7 +17,7 @@ The following metrics uses LLM to identify if a retrieved context is relevant or

### Context Precision without reference

`LLMContextPrecisionWithoutReference` metric can be used when you have both retrieved contexts and also reference contexts associated with a `user_input`. To estimate if a retrieved contexts is relevant or not this method uses the LLM to compare each of the retrieved context or chunk present in `retrieved_contexts` with `response`.
`LLMContextPrecisionWithoutReference` metric can be used when you have both retrieved contexts and also reference answer associated with a `user_input`. To estimate if a retrieved contexts is relevant or not this method uses the LLM to compare each of the retrieved context or chunk present in `retrieved_contexts` with `response`.

#### Example

Expand All @@ -43,7 +43,7 @@ Output

### Context Precision with reference

`LLMContextPrecisionWithReference` metric is can be used when you have both retrieved contexts and also reference answer associated with a `user_input`. To estimate if a retrieved contexts is relevant or not this method uses the LLM to compare each of the retrieved context or chunk present in `retrieved_contexts` with `reference`.
`LLMContextPrecisionWithReference` metric is can be used when you have both retrieved contexts and also reference context associated with a `user_input`. To estimate if a retrieved contexts is relevant or not this method uses the LLM to compare each of the retrieved context or chunk present in `retrieved_contexts` with `reference`.

#### Example

Expand Down Expand Up @@ -92,4 +92,4 @@ await context_precision.single_turn_ascore(sample)
Output
```
0.9999999999
```
```