Comments (3)
Hi Dave, currently we don't have any paragraph detection. A naive regex-based approach would be relatively easy to add using basically the same approach for sections, but this would probably only be based on double newlines.
I've had ideas for unsupervised approaches for paragraph splitting but it would be experimental until we could verify it with manually annotated gold standards. I'll bring it up at one of our planning meetings.
from biomedicus.
Thanks, Ben!
from biomedicus.
FYI. We added our own paragraph identifications along the lines you mention above. So this is a lower priority item for our team. We can close the feature request unless you'd like to keep it.
from biomedicus.
Related Issues (20)
- Intermittent deployment test failure
- Deploying rtf to text downloads models unnecessarily
- RTF is missing a number of control keywords that output characters
- RTF is missing the /v hidden text character formatting keyword
- Mismatched dependencies to sentences in stanza_selective_parser.
- Sentences processor fails to run when CUDA available
- Bump minimum required Python to 3.8
- Add command line flag to "b9 deploy" for service launch timeout
- Deepen processor runs with mp=True by default HOT 1
- Switch the default negation detection to negex only HOT 1
- Daemonize Service Deployment
- MTAP 1.2.1 Compatibility
- Automatically build and publish to PyPI and GHCR
- Multiple annotations for same span with/without leading punctuation HOT 4
- Add ICD10CM to the Concepts UMLS Sources HOT 1
- New versions of numpy >=1.25.0 require Python >=3.9
- b9-REST
- Enhanced section detection
- Create pipeline component to detect blown-in/injected data
- Default "--host" argument value in deploy overwrites any deployment configuration
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from biomedicus.