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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. ideally provide more context for entities stored in the KB.
`spacy-llm` provides a `CandidateSelector` implementation `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 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 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. doesn't have to be trained) or from a separate .yaml file.
@ -359,7 +359,7 @@ candidate.
| Argument | Description | | 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]]~~ | | `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]]~~ | | `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~~ | | `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 | | 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.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.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. | | [`spacy.NER.v2`](/api/large-language-models#ner-v2) | Builds on v1 and additionally supports defining the provided labels with explicit descriptions. |