Clean patterns pipeline for English

Description

The clean_pattern 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

Live Demo Open in Colab Download Copy S3 URI

How to use

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

val pipeline = new PretrainedPipeline("clean_pattern", 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.clean.pattern').predict(text)
result_df

Results

Results



|    | document   | sentence   | token     | normal    |
|---:|:-----------|:-----------|:----------|:----------|
|  0 | ['Hello']  | ['Hello']  | ['Hello'] | ['Hello'] ||    | document                         | sentence                        | token                                          | normal                                    |


{:.model-param}

Model Information

Included Models

• DocumentAssembler
• SentenceDetector
• TokenizerModel
• NormalizerModel