Description
This model annotates the part of speech of tokens in a text. The parts of speech annotated include PRON (pronoun), CCONJ (coordinating conjunction), and 15 others. The part of speech model is useful for extracting the grammatical structure of a piece of text automatically.
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How to use
...
pos = PerceptronModel.pretrained("pos_ud_gsd", "es") \
.setInputCols(["document", "token"]) \
.setOutputCol("pos")
nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, pos])
light_pipeline = LightPipeline(nlp_pipeline.fit(spark.createDataFrame([['']]).toDF("text")))
results = light_pipeline.fullAnnotate("Además de ser el rey del norte, John Snow es un médico inglés y líder en el desarrollo de la anestesia y la higiene médica.")
...
val pos = PerceptronModel.pretrained("pos_ud_gsd", "es")
.setInputCols(Array("document", "token"))
.setOutputCol("pos")
val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, pos))
val data = Seq("Además de ser el rey del norte, John Snow es un médico inglés y líder en el desarrollo de la anestesia y la higiene médica.").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
text = ["""Además de ser el rey del norte, John Snow es un médico inglés y líder en el desarrollo de la anestesia y la higiene médica."""]
pos_df = nlu.load('es.pos.ud_gsd').predict(text, output_level='token')
pos_df
Results
[Row(annotatorType='pos', begin=0, end=5, result='ADV', metadata={'word': 'Además'}),
Row(annotatorType='pos', begin=7, end=8, result='ADP', metadata={'word': 'de'}),
Row(annotatorType='pos', begin=10, end=12, result='AUX', metadata={'word': 'ser'}),
Row(annotatorType='pos', begin=14, end=15, result='DET', metadata={'word': 'el'}),
Row(annotatorType='pos', begin=17, end=19, result='NOUN', metadata={'word': 'rey'}),
...]
Model Information
Model Name: | pos_ud_gsd |
Type: | pos |
Compatibility: | Spark NLP 2.4.0 |
Edition: | Official |
Input labels: | [token] |
Output labels: | [pos] |
Language: | es |
Case sensitive: | false |
License: | Open Source |
Data Source
The model is imported from https://universaldependencies.org
PREVIOUSSpanish Lemmatizer