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Changelog
Added
Support for a
filesystem
parameter in everyedsnlp.data.read_*
andedsnlp.data.write_*
functionsPipes of a pipeline are now easily accessible with
nlp.pipes.xxx
instead ofnlp.get_pipe("xxx")
Support builtin Span attributes in converters
span_attributes
parameter, e.g.Support assigning Brat AnnotatorNotes as span attributes:
edsnlp.data.read_standoff(..., notes_as_span_attribute="cui")
Support for mapping full batches in
edsnlp.processing
pipelines withmap_batches
lazy collection method:New
data.map_gpu
method to map a deep learning operation on some data and take advantage of edsnlp multi-gpu inference capabilitiesAdded average precision computation in edsnlp span_classification scorer
You can now add pipes to your pipeline by instantiating them directly, which comes with many advantages, such as auto-completion, introspection and type checking !
The previous way of adding pipes is still supported.
New
eds.span_linker
deep-learning component to match entities with their concepts in a knowledge base, in synonym-similarity or concept-similarity mode.Changed
nlp.preprocess_many
now uses lazy collections to enable parallel processingeds.span_qualifier
: we didn't support combination groups before, so this feature was scrapped for now. We now also support splitting values of a single qualifier between different span labels.__init__
signature. For most components of EDS-NLP, this will change the name from "eds.xxx" to "xxx".Fixed
nlp.map(data).to_iterable("ents")
is now a list of entities, and not a list of lists of entitieseds.transformer
) by sorting them by Dice overlap score.