Recognize Entities DL Pipeline for Spanish - Small


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 = 'es')
annotations =  pipeline.fullAnnotate(""Hola de John Snow Labs! "")[0]

val pipeline = new PretrainedPipeline("entity_recognizer_sm", lang = "es")
val result = pipeline.fullAnnotate("Hola de John Snow Labs! ")(0)

import nlu
text = [""Hola de John Snow Labs! ""]
result_df = nlu.load('es.ner').predict(text)


|    | document                     | sentence                    | token                                   | embeddings                   | ner                                    | entities               |
|  0 | ['Hola de John Snow Labs! '] | ['Hola de John Snow Labs!'] | ['Hola', 'de', 'John', 'Snow', 'Labs!'] | [[0.1754499971866607,.,...]] | ['O', 'O', 'B-PER', 'I-PER', 'B-MISC'] | ['John Snow', 'Labs!'] |

Model Information

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