Description
This pretrained pipeline is built on the top of roberta_token_classifier_timex_semeval model.
Predicted Entities
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How to use
timex_pipeline = PretrainedPipeline("roberta_token_classifier_timex_semeval_pipeline", lang = "en")
timex_pipeline.annotate("Model training was started at 22:12C and it took 3 days from Tuesday to Friday.")
val timex_pipeline = new PretrainedPipeline("roberta_token_classifier_timex_semeval_pipeline", lang = "en")
timex_pipeline.annotate("Model training was started at 22:12C and it took 3 days from Tuesday to Friday.")
Results
+-------+-----------------+
|chunk |ner_label |
+-------+-----------------+
|22:12C |Period |
|3 |Number |
|days |Calendar-Interval|
|Tuesday|Day-Of-Week |
|to |Between |
|Friday |Day-Of-Week |
+-------+-----------------+
Model Information
| Model Name: | roberta_token_classifier_timex_semeval_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 4.0.0+ |
| License: | Open Source |
| Edition: | Community |
| Language: | en |
| Size: | 439.5 MB |
Included Models
- DocumentAssembler
- SentenceDetector
- TokenizerModel
- RoBertaForTokenClassification
- NerConverter
- Finisher