Part of Speech for Polish

Description

A Part of Speech classifier predicts a grammatical label for every token in the input text. Implemented with an averaged perceptron architecture.

Predicted Entities

  • ADJ
  • ADP
  • ADV
  • AUX
  • CCONJ
  • DET
  • NOUN
  • NUM
  • PART
  • PRON
  • PROPN
  • PUNCT
  • VERB

Live Demo Open in Colab Download

How to use

document_assembler = DocumentAssembler()\
  .setInputCol("text")\
  .setOutputCol("document")

sentence_detector = SentenceDetector()\
  .setInputCols(["document"])\
  .setOutputCol("sentence")

pos = PerceptronModel.pretrained("pos_lfg", "pl")\
  .setInputCols(["document", "token"])\
  .setOutputCol("pos")

pipeline = Pipeline(stages=[
  document_assembler,
  sentence_detector,
  posTagger
])

example = spark.createDataFrame(pd.DataFrame({'text': ["Zarobki wszystkich nauczycieli będą rosły co rok ."]}))
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_lfg", "pl")
        .setInputCols(Array("document", "token"))
        .setOutputCol("pos")

val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, pos))

val result = pipeline.fit(Seq.empty["Zarobki wszystkich nauczycieli będą rosły co rok ."].toDS.toDF("text")).transform(data)

import nlu

text = [""Zarobki wszystkich nauczycieli będą rosły co rok .""]
token_df = nlu.load('pl.pos.lfg').predict(text)
token_df

Results

+--------------------------------------------------+----------------------------------------------+
|text                                              |result                                        |
+--------------------------------------------------+----------------------------------------------+
|Zarobki wszystkich nauczycieli będą rosły co rok .|[NOUN, DET, NOUN, AUX, VERB, ADP, NOUN, PUNCT]|
+--------------------------------------------------+----------------------------------------------+

Model Information

Model Name: pos_lfg
Compatibility: Spark NLP 2.7.5+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [pos]
Language: pl

Data Source

The model was trained on the Universal Dependencies data set.

Benchmarking

|              | precision | recall | f1-score | support |
|--------------|-----------|--------|----------|---------|
| ADJ          | 0.93      | 0.90   | 0.92     | 830     |
| ADP          | 0.98      | 0.99   | 0.99     | 1097    |
| ADV          | 0.91      | 0.94   | 0.93     | 589     |
| AUX          | 0.93      | 0.95   | 0.94     | 429     |
| CCONJ        | 0.98      | 0.99   | 0.98     | 354     |
| DET          | 0.94      | 0.91   | 0.93     | 324     |
| INTJ         | 0.67      | 0.33   | 0.44     | 6       |
| NOUN         | 0.93      | 0.95   | 0.94     | 2457    |
| NUM          | 0.92      | 0.94   | 0.93     | 90      |
| PART         | 0.99      | 0.95   | 0.97     | 597     |
| PRON         | 0.98      | 0.97   | 0.97     | 986     |
| PROPN        | 0.92      | 0.87   | 0.89     | 470     |
| PUNCT        | 1.00      | 1.00   | 1.00     | 2555    |
| SCONJ        | 0.97      | 0.99   | 0.98     | 141     |
| VERB         | 0.96      | 0.96   | 0.96     | 2187    |
| accuracy     |           |        | 0.96     | 13112   |
| macro avg    | 0.93      | 0.91   | 0.92     | 13112   |
| weighted avg | 0.96      | 0.96   | 0.96     | 13112   |
| weighted avg | 0.92      | 0.92   | 0.92     | 139697  |