Whether to remove all the existing annotation columns (Default: true
)
Whether to remove all the existing annotation columns (Default: true
)
Name of EmbeddingsFinisher output cols
If enabled it will output the embeddings as Vectors instead of arrays (Default: false
)
Name of input annotation cols containing embeddings
Name of input annotation cols containing embeddings
If enabled it will output the embeddings as Vectors instead of arrays (Default: false
)
Name of EmbeddingsFinisher output cols
Whether to remove all the existing annotation columns (Default: true
)
Name of input annotation cols containing embeddings
Name of input annotation cols containing embeddings
If enabled it will output the embeddings as Vectors instead of arrays (Default: false
)
Name of EmbeddingsFinisher output cols
Name of EmbeddingsFinisher output cols
required uid for storing annotator to disk
required uid for storing annotator to disk
A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.
Extracts embeddings from Annotations into a more easily usable form.
This is useful for example: WordEmbeddings, BertEmbeddings, SentenceEmbeddings and ChunkEmbeddings.
By using
EmbeddingsFinisher
you can easily transform your embeddings into array of floats or vectors which are compatible with Spark ML functions such as LDA, K-mean, Random Forest classifier or any other functions that requirefeatureCol
.For more extended examples see the Spark NLP Workshop.
Example
Finisher for finishing Strings