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Raphael Mitsch 2023-11-29 10:10:13 +01:00
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website/docs/api/large-language-models.mdx
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@ -322,7 +322,7 @@ fetch descriptions for any given entity ID. Descriptions can be empty, but
ideally provide more context for entities stored in the KB.
`spacy-llm` provides a `CandidateSelector` implementation
(`spacy.CandidateSelector.v1`) that leverages a spaCy knowledge base -as used
(`spacy.CandidateSelector.v1`) that leverages a spaCy knowledge base - as used
in an `entity_linking` component - to select candidates. This knowledge base can
be loaded from an existing spaCy pipeline (note that the pipeline's EL component
doesn't have to be trained) or from a separate .yaml file.
@ -359,7 +359,7 @@ candidate.
| Argument | Description |
| --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `template` | Custom prompt template to send to LLM model. Defaults to [ner.v3.jinja](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/ner.v3.jinja). ~~str~~ |
| `template` | Custom prompt template to send to LLM model. Defaults to [entity_linker.v1.jinja](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/entity_linker.v1.jinja). ~~str~~ |
| `parse_responses` | Callable for parsing LLM responses for this task. Defaults to the internal parsing method for this task. ~~Optional[TaskResponseParser[EntityLinkerTask]]~~ |
| `prompt_example_type` | Type to use for fewshot examples. Defaults to `ELExample`. ~~Optional[Type[FewshotExample]]~~ |
| `examples` | Optional callable that reads a file containing task examples for few-shot learning. If `None` is passed, zero-shot learning will be used. Defaults to `None`. ~~ExamplesConfigType~~ |

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website/docs/usage/large-language-models.mdx
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@ -357,7 +357,7 @@ evaluate the component.
| Component | Description |
| ----------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- |
| [`spacy.EntityLinker.v1`](/api/large-language-models#summarization-v1) | The entity linking task prompts the model to link all entities in a given text to entries in a knowledge base. |
| [`spacy.EntityLinker.v1`](/api/large-language-models#el-v1) | The entity linking task prompts the model to link all entities in a given text to entries in a knowledge base. |
| [`spacy.Summarization.v1`](/api/large-language-models#summarization-v1) | The summarization task prompts the model for a concise summary of the provided text. |
| [`spacy.NER.v3`](/api/large-language-models#ner-v3) | Implements Chain-of-Thought reasoning for NER extraction - obtains higher accuracy than v1 or v2. |
| [`spacy.NER.v2`](/api/large-language-models#ner-v2) | Builds on v1 and additionally supports defining the provided labels with explicit descriptions. |