medkit.core.text.operation#

Classes:

ContextOperation([uid, name])

Abstract operation for context detection.

CustomTextOpType(value)

Enum class listing all supported function types for creating custom text operations

NEROperation([uid, name])

Abstract operation for detecting entities.

SegmentationOperation([uid, name])

Abstract operation for segmenting text.

Functions:

create_text_operation(function, function_type)

Function for instanciating a custom test operation from a user-defined function
class ContextOperation(uid=None, name=None, **kwargs)[source]#

Abstract operation for context detection. It uses a list of segments as input for running the operation and creates attributes that are directly appended to these segments.

Common initialization for all annotators:

  • assigning identifier to operation

  • storing class name, name and config in description

Parameters

  • uid (str) – Operation identifier

  • name – Operation name (defaults to class name)

  • kwargs – All other arguments of the child init useful to describe the operation

Examples

In the __init__ function of your annotator, use:

>>> init_args = locals()
>>> init_args.pop('self')
>>> super().__init__(**init_args)
class NEROperation(uid=None, name=None, **kwargs)[source]#

Abstract operation for detecting entities. It uses a list of segments as input and produces a list of detected entities.

Common initialization for all annotators:

  • assigning identifier to operation

  • storing class name, name and config in description

Parameters

  • uid (str) – Operation identifier

  • name – Operation name (defaults to class name)

  • kwargs – All other arguments of the child init useful to describe the operation

Examples

In the __init__ function of your annotator, use:

>>> init_args = locals()
>>> init_args.pop('self')
>>> super().__init__(**init_args)
class SegmentationOperation(uid=None, name=None, **kwargs)[source]#

Abstract operation for segmenting text. It uses a list of segments as input and produces a list of new segments.

Common initialization for all annotators:

  • assigning identifier to operation

  • storing class name, name and config in description

Parameters

  • uid (str) – Operation identifier

  • name – Operation name (defaults to class name)

  • kwargs – All other arguments of the child init useful to describe the operation

Examples

In the __init__ function of your annotator, use:

>>> init_args = locals()
>>> init_args.pop('self')
>>> super().__init__(**init_args)
class CustomTextOpType(value)[source]#

Enum class listing all supported function types for creating custom text operations

Variables

  • CREATE_ONE_TO_N – Takes 1 data item, Return N new data items

  • EXTRACT_ONE_TO_N – Takes 1 data item, Return N existing data items

  • FILTER – Takes 1 data item, Returns True/False

create_text_operation(function, function_type, name=None)[source]#

Function for instanciating a custom test operation from a user-defined function

Parameters

  • function (Callable) – User-defined function

  • function_type (CustomTextOpType) – Type of function. Supported values are defined in CustomTextOpType

  • name (Optional[str]) – Name of the operation used for provenance info (default: function name)

Return type

_CustomTextOperation

Returns

operation – An instance of a custom text operation