Recognize Entities OntoNotes pipeline - ELECTRA Small

Description

The onto_recognize_entities_electra_small is a pretrained pipeline that we can use to process text with a simple pipeline that performs basic processing steps. It performs most of the common text processing tasks on your dataframe

Predicted Entities

Download Copy S3 URI

How to use

from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('onto_recognize_entities_electra_small', lang = 'en')
annotations =  pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
annotations.keys()
val pipeline = new PretrainedPipeline("onto_recognize_entities_electra_small", lang = "en")
val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
import nlu
text = [""Hello from John Snow Labs ! ""]
result_df = nlu.load('en.ner.onto.electra.small').predict(text)
result_df

Results

Results


|    | document                         | sentence                        | token                                          | embeddings                   | ner                                        | entities           |
|---:|:---------------------------------|:--------------------------------|:-----------------------------------------------|:-----------------------------|:-------------------------------------------|:-------------------|
|  0 | ['Hello from John Snow Labs ! '] | ['Hello from John Snow Labs !'] | ['Hello', 'from', 'John', 'Snow', 'Labs', '!'] | [[0.2279076874256134,.,...]] | ['O', 'O', 'B-ORG', 'I-ORG', 'I-ORG', 'O'] | ['John Snow Labs'] |


{:.model-param}

Model Information

Model Name: onto_recognize_entities_electra_small
Type: pipeline
Compatibility: Spark NLP 4.4.2+
License: Open Source
Edition: Official
Language: en
Size: 66.3 MB

Included Models

  • DocumentAssembler
  • SentenceDetectorDLModel
  • TokenizerModel
  • BertEmbeddings
  • NerDLModel
  • NerConverter