Description
Part of Speech trained for English trained Pos Anc dataset. Predicts the following tags :
How to use
document_assembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
sentence_detector = SentenceDetector() \
.setInputCols(["document"]) \
.setOutputCol("sentence")
pos = PerceptronModel.pretrained("pos_anc", "en") \
.setInputCols(["document", "token"]) \
.setOutputCol("pos")
pipeline = Pipeline(stages=[
document_assembler,
sentence_detector,
posTagger
])
example = spark.createDataFrame([['Hello from John Snow Labs!']], ["text"])
result = pipeline.fit(example).transform(example)
val document_assembler = DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val sentence_detector = SentenceDetector()
.setInputCols("document")
.setOutputCol("sentence")
val pos = PerceptronModel.pretrained("pos_anc", "en")
.setInputCols(Array("document", "token"))
.setOutputCol("pos")
val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, pos))
val data = Seq("Hello from John Snow Labs!").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
text = ["Hello from John Snow Labs!"]
pos_df = nlu.load('en.pos.anc').predict(text, output_level = "token")
pos_df
Results
+----------+----------+
|token_result|pos_result|
+----------+----------+
|Hello |UH |
|from |IN |
|John |NNP |
|Snow |NNP |
|Labs |NNP |
|! |. |
+----------+----------+
Model Information
| Model Name: | pos_anc |
| Compatibility: | Spark NLP 3.0.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document, token] |
| Output Labels: | [pos] |
| Language: | en |