Recognize Entities DL pipeline for Italian - Large

Description

The entity_recognizer_lg 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

Download Copy S3 URI

How to use


from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('entity_recognizer_lg', lang = 'it')
annotations =  pipeline.fullAnnotate(""Ciao da John Snow Labs! "")[0]
annotations.keys()


val pipeline = new PretrainedPipeline("entity_recognizer_lg", lang = "it")
val result = pipeline.fullAnnotate("Ciao da John Snow Labs! ")(0)



import nlu
text = [""Ciao da John Snow Labs! ""]
result_df = nlu.load('it.ner.lg').predict(text)
result_df
    
from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('entity_recognizer_lg', lang = 'it')
annotations =  pipeline.fullAnnotate(""Ciao da John Snow Labs! "")[0]
annotations.keys()
val pipeline = new PretrainedPipeline("entity_recognizer_lg", lang = "it")
val result = pipeline.fullAnnotate("Ciao da John Snow Labs! ")(0)
import nlu
text = [""Ciao da John Snow Labs! ""]
result_df = nlu.load('it.ner.lg').predict(text)
result_df

Results

Results


|    | document                     | sentence                    | token                                   | embeddings                   | ner                                   | entities            |
|---:|:-----------------------------|:----------------------------|:----------------------------------------|:-----------------------------|:--------------------------------------|:--------------------|
|  0 | ['Ciao da John Snow Labs! '] | ['Ciao da John Snow Labs!'] | ['Ciao', 'da', 'John', 'Snow', 'Labs!'] | [[-0.238279998302459,.,...]] | ['O', 'O', 'I-PER', 'I-PER', 'I-PER'] | ['John Snow Labs!'] |


{:.model-param}

Model Information

Model Name: entity_recognizer_lg
Type: pipeline
Compatibility: Spark NLP 4.4.2+
License: Open Source
Edition: Official
Language: it
Size: 2.5 GB

Included Models

  • DocumentAssembler
  • SentenceDetector
  • TokenizerModel
  • WordEmbeddingsModel
  • NerDLModel
  • NerConverter