Recognize Entities DL Pipeline for Polish - Small

Description

The entity_recognizer_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('entity_recognizer_sm', lang = 'pl')
annotations =  pipeline.fullAnnotate(""Witaj z John Snow Labs! "")[0]
annotations.keys()


val pipeline = new PretrainedPipeline("entity_recognizer_sm", lang = "pl")
val result = pipeline.fullAnnotate("Witaj z John Snow Labs! ")(0)



import nlu
text = [""Witaj z John Snow Labs! ""]
result_df = nlu.load('pl.ner').predict(text)
result_df
    

Results

|    | document                     | sentence                    | token                                   | embeddings                   | ner                                   | entities            |
|---:|:-----------------------------|:----------------------------|:----------------------------------------|:-----------------------------|:--------------------------------------|:--------------------|
|  0 | ['Witaj z John Snow Labs! '] | ['Witaj z John Snow Labs!'] | ['Witaj', 'z', 'John', 'Snow', 'Labs!'] | [[0.0, 0.0, 0.0, 0.0,.,...]] | ['O', 'O', 'B-PER', 'I-PER', 'I-PER'] | ['John Snow Labs!'] |

Model Information

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