Recognize Entities DL pipeline for English - Small

Description

The onto_recognize_entities_sm 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

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How to use


from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('onto_recognize_entities_sm', lang = 'en')
annotations =  pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
annotations.keys()


val pipeline = new PretrainedPipeline("onto_recognize_entities_sm", 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.sm').predict(text)
result_df
    

Results

|    | document                         | sentence                        | token                                          | embeddings                   | ner                                        | entities           |
|---:|:---------------------------------|:--------------------------------|:-----------------------------------------------|:-----------------------------|:-------------------------------------------|:-------------------|
|  0 | ['Hello from John Snow Labs ! '] | ['Hello from John Snow Labs !'] | ['Hello', 'from', 'John', 'Snow', 'Labs', '!'] | [[0.2668800055980682,.,...]] | ['O', 'O', 'B-ORG', 'I-ORG', 'I-ORG', 'O'] | ['John Snow Labs'] |

Model Information

Model Name: onto_recognize_entities_sm
Type: pipeline
Compatibility: Spark NLP 3.0.0+
License: Open Source
Edition: Official
Language: en