Description
This is a Legal pretrained pipeline, aimed to carry out Section Splitting by using the Headers and Subheaders entities, detected in the document.
How to use
legal_pipeline = nlp.PretrainedPipeline("legpipe_header_subheader", "en", "legal/models")
text = ["""2. DEFINITION.
For purposes of this Agreement, the following terms have the meanings ascribed thereto in this Section 1 and 2 Appointment as Reseller.
2.1 Appointment.
The Company hereby [***]. Allscripts may also disclose Company's pricing information relating to its Merchant Processing Services and facilitate procurement of Merchant Processing Services on behalf of Sublicensed Customers, including, without limitation by references to such pricing information and Merchant Processing Services in Customer Agreements. 6
2.2 Customer Agreements."""]
result = legal_pipeline.annotate(text)
Results
| chunks | begin | end | entities |
|------------------------:|------:|----:|----------:|
| 2. DEFINITION | 0 | 12 | HEADER |
| 2.1 Appointment | 154 | 168 | SUBHEADER |
| 2.2 Customer Agreements | 530 | 552 | SUBHEADER |
Model Information
| Model Name: | legpipe_header_subheader |
| Type: | pipeline |
| Compatibility: | Legal NLP 1.0.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 23.6 KB |
Included Models
- DocumentAssembler
- TokenizerModel
- ContextualParserModel
- ContextualParserModel
- ChunkMergeModel