Description
Pretrained Lemmatizer model (lemma_perseus) trained on Universal Dependencies 2.9 (UD_Latin-Perseus) in Latin language.
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How to use
document = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
sentence = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
.setInputCols(["document"])\
.setOutputCol("sentence")
tokenizer = Tokenizer()\
.setInputCols(["sentence"])\
.setOutputCol("token")
lemma = LemmatizerModel.pretrained("lemma_perseus", "la")\
.setInputCols(["token"])\
.setOutputCol("lemma")
pipeline = Pipeline(stages=[document, sentence, tokenizer, lemma])
data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
result = pipeline.fit(data).transform(data)
Model Information
| Model Name: | lemma_perseus |
| Compatibility: | Spark NLP 3.4.3+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [form] |
| Output Labels: | [lemma] |
| Language: | la |
| Size: | 123.5 KB |
References
Model is trained on Universal Dependencies (treebank 2.9) UD_Latin-Perseus