TokenSearcherNER

NER task

This task uses TokenSearcherPredictor by default. For more details, see:

TokenSearcherPredictor

Subclass of NERTask.

Module: implementation.tasks

Methods and properties

Main methods and properties

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__init__

Arguments:

• predictor (Predictor[Any, Any], optional): Predictor that will be used in task. If equals to None, default TokenSearcherPredictor will be used. Defaults to None.

• preprocess (Optional[Component], optional): Component executed before predictor. If equals to None, default component will be used. Defaults to None. Default component: TokenSearcherNERPreprocessor

• postprocess (Optional[Component], optional): Component executed after predictor. If equals to None, default component will be used. Defaults to None. Default component: TokenSearcherNERPostprocessor

• input_class (Type[Input], optional): Class for input validation. Defaults to TokenSearcherNERInput.

• output_class (Type[NEROutputType], optional): Class for output validation. Defaults to TokenSearcherNEROutput.

• name (Optional[str], optional): Name for identification. If equals to None, class name will be used. Defaults to None.

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TokenSearcherNERInput

Subclass of IOModel.

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__init__

Arguments:

• text (str): Text to clean.

• labels (List[str]): Labels for classification.

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TokenSearcherNEROutput

Subclass of NEROutput. Type of NEROutput[ClassifiedEntity].

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__init__

Arguments:

• text (str): Input text.

• output (List[ClassifiedEntity]): Classified entities.

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TokenSearcherNERPreprocessor

Create prompts with providied text. Subclass of Action. Type of Action[Dict[str, Any], Dict[str, Any]].

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__init__

Arguments:

• sents_batch (int): Chunks size in sentences. Defaults to 10.

• name (Optional[str], optional): Name for identification. If equals to None, class name will be used. Defaults to None.

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execute

Arguments:

• input_data (Dict[str, Any]): Expected keys:

  • "text" (str): Text to process;

  • "labels" (List[str]): Labels for classification;

Returns:

• Dict[str, Any]: Expected keys:

  • "inputs" (List[str]): Model inputs;

  • "chunks_starts" (List[int]): Chunks start positions. Used by postprocessor;

  • "prompt_lengths" (List[int]): Prompt lenghts. Used by postprocessor;

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TokenSearcherNERPostprocessor

Format output. Subclass of Action. Type of Action[Dict[str, Any], Dict[str, Any]].

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__init__

Arguments:

• threshold (float): Entities threshold score. Defaults to 0.

• name (Optional[str], optional): Name for identification. If equals to None, class name will be used. Defaults to None.

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execute

Arguments:

• input_data (Dict[str, Any]): Expected keys:

  • "output" (List[List[Dict[str, Any]]]): Model output;

  • "labels" (List[str]): Labels for classification;

  • "text" (str): Processed text;

  • "chunks_starts" (List[int]): Chunks start positions;

  • "prompt_lengths" (List[int]): Prompt lenghts;

Returns:

• Dict[str, Any]: Expected keys:

  • "text" (str): Processed text;

  • "output" (List[ClassifiedEntity]): Classified entities;

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