Explain Document ML Pipeline for English

Description

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

Predicted Entities

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How to use



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


val pipeline = new PretrainedPipeline("explain_document_ml", 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.explain').predict(text)
result_df

Results


|    | document                         | sentence                         | token                                            | spell                                           | lemmas                                          | stems                                          | pos                                    |
|---:|:---------------------------------|:---------------------------------|:-------------------------------------------------|:------------------------------------------------|:------------------------------------------------|:-----------------------------------------------|:---------------------------------------|
|  0 | ['Hello fronm John Snwow Labs!'] | ['Hello fronm John Snwow Labs!'] | ['Hello', 'fronm', 'John', 'Snwow', 'Labs', '!'] | ['Hello', 'front', 'John', 'Snow', 'Labs', '!'] | ['Hello', 'front', 'John', 'Snow', 'Labs', '!'] | ['hello', 'front', 'john', 'snow', 'lab', '!'] | ['UH', 'NN', 'NNP', 'NNP', 'NNP', '.'] ||    | document   | sentence   | token     | spell     | lemmas    | stems     | pos    |

Model Information

Model Name: explain_document_ml
Type: pipeline
Compatibility: Spark NLP 4.0.0+
License: Open Source
Edition: Official
Language: en
Size: 9.6 MB

Included Models

  • DocumentAssembler
  • SentenceDetector
  • TokenizerModel
  • NorvigSweetingModel
  • LemmatizerModel
  • Stemmer
  • PerceptronModel