medkit.text.spacy.edsnlp#

This package needs extra-dependencies not installed as core dependencies of medkit. To install them, use pip install medkit[edsnlp].

Classes:

EDSNLPDocPipeline(nlp[, medkit_labels_anns, ...])

DocPipeline to obtain annotations created using EDS-NLP

EDSNLPPipeline(nlp[, spacy_entities, ...])

Segment annotator relying on an EDS-NLP pipeline

Functions:

build_context_attribute(spacy_span, spacy_label)

Build a medkit attribute from an EDS-NLP context/qualifying attribute, adding the cues as metadata

build_date_attribute(spacy_span, spacy_label)

Build a medkit date attribute from an EDS-NLP attribute with a date object as value.

build_history_attribute(spacy_span, spacy_label)

Build a medkit attribute from an EDS-NLP "history" attribute, adding the cues as metadata

build_score_attribute(spacy_span, spacy_label)

Build a medkit attribute from an EDS-NLP "score_name" and corresponding "score_value" attribute.

build_value_attribute(spacy_span, spacy_label)

Build a medkit attribute from an EDS-NLP "value" attribute with a custom object as value:

Data:

DEFAULT_ATTRIBUTE_FACTORIES

Pre-defined attribute factories to handle EDS-NLP attributes
class EDSNLPPipeline(nlp, spacy_entities=None, spacy_span_groups=None, spacy_attrs=None, medkit_attribute_factories=None, name=None, uid=None)[source]#

Segment annotator relying on an EDS-NLP pipeline

Initialize the segment annotator

Parameters

  • nlp (Language) – Language object with the loaded pipeline from Spacy

  • spacy_entities (Optional[List[str]]) – Labels of new spacy entities (doc.ents) to convert into medkit entities. If None (default) all the new spacy entities will be converted

  • spacy_span_groups (Optional[List[str]]) – Name of new spacy span groups (doc.spans) to convert into medkit segments. If None (default) new spacy span groups will be converted

  • spacy_attrs (Optional[List[str]]) – Name of span extensions to convert into medkit attributes. If None, all non-redundant EDS-NLP attributes will be handled.

  • medkit_attribute_factories (Optional[Dict[str, Callable[[Span, str], Attribute]]]) – Mapping of factories in charge of converting spacy attributes to medkit attributes. Factories will receive a spacy span and an an attribute label when called. The key in the mapping is the attribute label. Pre-defined default factories are listed in DEFAULT_ATTRIBUTE_FACTORIES

  • name (Optional[str]) – Name describing the pipeline (defaults to the class name).

  • uid (str) – Identifier of the pipeline

class EDSNLPDocPipeline(nlp, medkit_labels_anns=None, medkit_attrs=None, spacy_entities=None, spacy_span_groups=None, spacy_attrs=None, medkit_attribute_factories=None, name=None, uid=None)[source]#

DocPipeline to obtain annotations created using EDS-NLP

Initialize the pipeline

Parameters

  • nlp (Language) – Language object with the loaded pipeline from Spacy

  • medkit_labels_anns (Optional[List[str]]) – Labels of medkit annotations to include in the spacy document. If None (default) all the annotations will be included.

  • medkit_attrs (Optional[List[str]]) – Labels of medkit attributes to add in the annotations that will be included. If None (default) all the attributes will be added as custom attributes in each annotation included.

  • spacy_entities (Optional[List[str]]) – Labels of new spacy entities (doc.ents) to convert into medkit entities. If None (default) all the new spacy entities will be converted and added into its origin medkit document.

  • spacy_span_groups (Optional[List[str]]) – Name of new spacy span groups (doc.spans) to convert into medkit segments. If None (default) new spacy span groups will be converted and added into its origin medkit document.

  • spacy_attrs (Optional[List[str]]) – Name of span extensions to convert into medkit attributes. If None, all non-redundant EDS-NLP attributes will be handled.

  • medkit_attribute_factories (Optional[Dict[str, Callable[[Span, str], Attribute]]]) – Mapping of factories in charge of converting spacy attributes to medkit attributes. Factories will receive a spacy span and an an attribute label when called. The key in the mapping is the attribute label. Pre-defined default factories are listed in DEFAULT_ATTRIBUTE_FACTORIES

  • name (Optional[str]) – Name describing the pipeline (defaults to the class name).

  • uid (str) – Identifier of the pipeline

build_date_attribute(spacy_span, spacy_label)[source]#

Build a medkit date attribute from an EDS-NLP attribute with a date object as value.

Parameters

  • spacy_span (Span) – Spacy span having an ESD-NLP date attribute

  • spacy_label (str) – Label of the date attribute on spacy_spacy. Ex: “date”, “consultation_date”

Return type

Attribute

Returns

Attribute – DateAttribute, RelativeDateAttribute or DurationAttribute instance, depending on the EDS-NLP attribute

build_value_attribute(spacy_span, spacy_label)[source]#

Build a medkit attribute from an EDS-NLP “value” attribute with a custom object as value:

  • if the value is an EDS-NLP Adipcap object, a ADICAPNormAttribute instance is returned;

  • if the value is an EDS-NLP TNN object, a TNMAttribute instance is returned;

  • if the value is an EDS-NLP SimpleMeasurement object, a Attribute instance is returned.

Otherwise an error is raised.

Parameters

  • spacy_span (Span) – Spacy span having an attribute custom object as value

  • spacy_label (str) – Label of the attribute on spacy_spacy. Ex: “value”

Return type

Attribute

Returns

Attribute – Medkit attribute corresponding to the spacy attribute value

build_score_attribute(spacy_span, spacy_label)[source]#

Build a medkit attribute from an EDS-NLP “score_name” and corresponding “score_value” attribute.

Parameters

  • spacy_span (Span) – Spacy span having “score_name” and “score_value” attributes

  • spacy_label (str) – Must be “score_name”

Return type

Attribute

Returns

Attribute – Medkit attribute with “score_name” value as label and “score_value” value as value

build_context_attribute(spacy_span, spacy_label)[source]#

Build a medkit attribute from an EDS-NLP context/qualifying attribute, adding the cues as metadata

Parameters

  • spacy_span (Span) – Spacy span having a context/qualifying attribute

  • spacy_label (str) – Label of the attribute on spacy_spacy. Ex: “negation”, “hypothesis”, etc

Return type

Attribute

Returns

Attribute – Medkit attribute corresponding to the spacy attribute

build_history_attribute(spacy_span, spacy_label)[source]#

Build a medkit attribute from an EDS-NLP “history” attribute, adding the cues as metadata

Parameters

  • spacy_span (Span) – Spacy span having a “history” attribute

  • spacy_label (str) – Must be “history”

Return type

Attribute

Returns

Attribute – Medkit attribute corresponding to the spacy attribute

DEFAULT_ATTRIBUTE_FACTORIES = {'consultation_date': <function build_date_attribute>, 'date': <function build_date_attribute>, 'family': <function build_context_attribute>, 'history': <function build_history_attribute>, 'hypothesis': <function build_context_attribute>, 'negation': <function build_context_attribute>, 'reported_speech': <function build_context_attribute>, 'score_name': <function build_score_attribute>, 'value': <function build_value_attribute>}#

Pre-defined attribute factories to handle EDS-NLP attributes