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.
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 result = pipeline.fit(Seq.empty["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."].toDS.toDF("text")).transform(data)
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