Recognize Entities DL Pipeline for French - Medium

Description

The entity_recognizer_md 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('entity_recognizer_md', lang = 'fr')
annotations =  pipeline.fullAnnotate(""Bonjour de John Snow Labs! "")[0]
annotations.keys()


val pipeline = new PretrainedPipeline("entity_recognizer_md", lang = "fr")
val result = pipeline.fullAnnotate("Bonjour de John Snow Labs! ")(0)



import nlu
text = [""Bonjour de John Snow Labs! ""]
result_df = nlu.load('fr.ner.md').predict(text)
result_df

Results

|    | document                        | sentence                       | token                                      | embeddings                   | ner                                        | entities                       |
|---:|:--------------------------------|:-------------------------------|:-------------------------------------------|:-----------------------------|:-------------------------------------------|:-------------------------------|
|  0 | ['Bonjour de John Snow Labs! '] | ['Bonjour de John Snow Labs!'] | ['Bonjour', 'de', 'John', 'Snow', 'Labs!'] | [[0.0783179998397827,.,...]] | ['I-MISC', 'O', 'I-PER', 'I-PER', 'I-PER'] | ['Bonjour', 'John Snow Labs!'] |

Model Information

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