Description
The explain_document_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
Open in Colab Download Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('explain_document_sm', lang = 'pl')
annotations = pipeline.fullAnnotate(""Witaj z John Snow Labs! "")[0]
annotations.keys()
val pipeline = new PretrainedPipeline("explain_document_sm", lang = "pl")
val result = pipeline.fullAnnotate("Witaj z John Snow Labs! ")(0)
import nlu
text = [""Witaj z John Snow Labs! ""]
result_df = nlu.load('pl.explain').predict(text)
result_df
Results
| | document | sentence | token | lemma | pos | embeddings | ner | entities |
|---:|:-----------------------------|:----------------------------|:----------------------------------------|:----------------------------------------|:-------------------------------------------|:-----------------------------|:--------------------------------------|:--------------------|
| 0 | ['Witaj z John Snow Labs! '] | ['Witaj z John Snow Labs!'] | ['Witaj', 'z', 'John', 'Snow', 'Labs!'] | ['witać', 'z', 'John', 'Snow', 'Labs!'] | ['VERB', 'ADP', 'PROPN', 'PROPN', 'PROPN'] | [[0.0, 0.0, 0.0, 0.0,.,...]] | ['O', 'O', 'B-PER', 'I-PER', 'I-PER'] | ['John Snow Labs!'] |
Model Information
| Model Name: | explain_document_sm |
| Type: | pipeline |
| Compatibility: | Spark NLP 3.0.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | pl |