medkit.text.preprocessing.duplicate_finder
medkit.text.preprocessing.duplicate_finder#
Classes:
|
Detect duplicated chunks of text across a collection of text documents, relying on the duptextfinder library. |
|
Attribute indicating if some text is a duplicate of some other text in another document |
- class DuplicateFinder(output_label, segments_to_output='dup', min_duplicate_length=5, fingerprint_type='word', fingerprint_length=2, date_metadata_key=None, case_sensitive=True, allow_multiline=True, orf=1)[source]#
Detect duplicated chunks of text across a collection of text documents, relying on the duptextfinder library.
When a duplicated chunk of text is found, a segment is created on the newest document covering the span that is duplicated. A
DuplicationAttribute
having “is_duplicate” as label and True as value is attached to the segment. It can later be propagated to the entities created from the duplicate segments.The attribute also holds the id of the source document from which the text was copied, the spans of the text in the source document, and optionally the date of the source document if provided.
Optionally, segments can also be created for non-duplicate zones to make it easier to process only those parts of the documents. For these segments, the attribute value is False and the source, spans and date fields are None.
NB: better performance may be achieved by installing the ncls python package, which will then be used by duptextfinder library.
- Parameters
output_label (
str
) – Label of created segmentssegments_to_output (
Literal
['dup'
,'nondup'
,'both'
]) – Type of segments to create: only duplicate segments (“dup”), only non-duplicate segments (“nondup”), or both (“both”)min_duplicate_length (
int
) – Minimum length of duplicated segments, in characters (shorter segments will be discarded)fingerprint_type (
Literal
['char'
,'word'
]) – Base unit to use for fingerprinting (either “char” or “word”)fingerprint_length (
int
) – Number of chars or words in each fingerprint. If fingerprint_type is set to “char”, this should be the same value as min_duplicate_length. If fingerprint_type is set to “word”, this should be around the average word size multiplied by min_duplicate_lengthdate_metadata_key (
Optional
[str
]) – Key to use to retrieve the date of each document from their metadata dicts. When provided, this is used to determine which document should be the source of a duplicate (the older) and which document should be the recipient (the newer). If None, the order of the documents in the collection will be used.case_sensitive (
bool
) – Whether duplication detection should be case-sensitive or notallow_multiline (
bool
) – Whether detected duplicates can span across multiline lines, or each line should be handled separatelyorf (
int
) – Step size when building fingerprints, cf the duptextfinder documentation
Methods:
run
(collections)Find duplicates in each collection of documents
set_prov_tracer
(prov_tracer)Enable provenance tracing.
Attributes:
Contains all the operation init parameters.
- run(collections)[source]#
Find duplicates in each collection of documents
For each duplicate found, a
Segment
object with aDuplicationAttribute
will be created and attached to the document that is the recipient of the duplication (ie not the source document).
- property description: medkit.core.operation_desc.OperationDescription#
Contains all the operation init parameters.
- Return type
- set_prov_tracer(prov_tracer)#
Enable provenance tracing.
- Parameters
prov_tracer (
ProvTracer
) – The provenance tracer used to trace the provenance.
- class DuplicationAttribute(value, source_doc_id=None, source_spans=None, source_doc_date=None, metadata=None, uid=None)[source]#
Attribute indicating if some text is a duplicate of some other text in another document
- Variables
uid (str) – Identifier of the attribute
label (str) – The attribute label, always set to
DuplicationAttribute.LABEL
value (Optional[Any]) – True if the segment or entity to which the attribute belongs is a duplicate of the part of another document, False otherwise.
source_doc_id (Optional[str]) – Identifier of the document from which the text was copied
source_spans (Optional[List[medkit.core.text.span.AnySpan]]) – Spans of the duplicated text in the source document
source_doc_date (Optional[Any]) – Date of the source document, if known
Attributes:
Label used for all TNM attributes
Methods:
copy
()Create a new attribute that is a copy of the current instance, but with a new identifier
from_dict
(attr_dict)Creates an Attribute from a dict
get_subclass_for_data_dict
(data_dict)Return the subclass that corresponds to the class name found in a data dict
to_brat
()Return a value compatible with the brat format
to_spacy
()Return a value compatible with spaCy
- LABEL: ClassVar[str] = 'is_duplicate'#
Label used for all TNM attributes
- classmethod from_dict(attr_dict)[source]#
Creates an Attribute from a dict
- Parameters
attribute_dict (dict) – A dictionary from a serialized Attribute as generated by to_dict()
- Return type
Self
- copy()#
Create a new attribute that is a copy of the current instance, but with a new identifier
This is used when we want to duplicate an existing attribute onto a different annotation.
- Return type
- classmethod get_subclass_for_data_dict(data_dict)#
Return the subclass that corresponds to the class name found in a data dict
- Parameters
data_dict (
Dict
[str
,Any
]) – Data dict returned by the to_dict() method of a subclass (or of the base class itself)- Return type
Optional
[Type
[Self
]]- Returns
subclass – Subclass that generated data_dict, or None if data_dict correspond to the base class itself.
- to_brat()#
Return a value compatible with the brat format
- Return type
Optional
[Any
]
- to_spacy()#
Return a value compatible with spaCy
- Return type
Optional
[Any
]