Recognize Entities DL Pipeline for Russian - 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 = 'ru')
annotations =  pipeline.fullAnnotate(""Здравствуйте из Джона Снежных Лабораторий! "")[0]
annotations.keys()


val pipeline = new PretrainedPipeline("entity_recognizer_sm", lang = "ru")
val result = pipeline.fullAnnotate("Здравствуйте из Джона Снежных Лабораторий! ")(0)



import nlu
text = [""Здравствуйте из Джона Снежных Лабораторий! ""]
result_df = nlu.load('ru.ner').predict(text)
result_df

Results

|    | document                                        | sentence                                       | token                                                      | embeddings                   | ner                                   | entities                       |
|---:|:------------------------------------------------|:-----------------------------------------------|:-----------------------------------------------------------|:-----------------------------|:--------------------------------------|:-------------------------------|
|  0 | ['Здравствуйте из Джона Снежных Лабораторий! '] | ['Здравствуйте из Джона Снежных Лабораторий!'] | ['Здравствуйте', 'из', 'Джона', 'Снежных', 'Лабораторий!'] | [[0.0, 0.0, 0.0, 0.0,.,...]] | ['O', 'O', 'B-PER', 'I-PER', 'I-PER'] | ['Джона Снежных Лабораторий!'] |

Model Information

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