From eae32600275f2e0cff7e78d30884dddf55decb1c Mon Sep 17 00:00:00 2001 From: Nicolas Garneau Date: Fri, 6 May 2016 17:17:48 -0400 Subject: [PATCH] Generic type for the NER and little typo --- src/main/scala/nodes/nlp/NER.scala | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/main/scala/nodes/nlp/NER.scala b/src/main/scala/nodes/nlp/NER.scala index f7d7723f..797eb9ce 100644 --- a/src/main/scala/nodes/nlp/NER.scala +++ b/src/main/scala/nodes/nlp/NER.scala @@ -12,19 +12,19 @@ import workflow.Transformer * Here's an example: * {{{ * val model = epic.models.NerSelector.loadNer("en").get - * val NERmodel = NERModel(model).apply(data) + * val NER = NER(model).apply(data) * }}} * * @param model The NER model loaded from the Epic library */ -case class NER(@transient model: SemiCRF[Any, String]) - extends Transformer[Array[String], Segmentation[Any, String]] { +case class NER[T](@transient model: SemiCRF[T, String]) + extends Transformer[Array[String], Segmentation[T, String]] { - def apply(in: Array[String]): Segmentation[Any, String] = { + def apply(in: Array[String]): Segmentation[T, String] = { model.bestSequence(in.toIndexedSeq) } - override def apply(in: RDD[Array[String]]): RDD[Segmentation[Any, String]] = { + override def apply(in: RDD[Array[String]]): RDD[Segmentation[T, String]] = { val modelBroadcast = in.sparkContext.broadcast(model) in.map(s => modelBroadcast.value.bestSequence(s.toIndexedSeq)) }