com.johnsnowlabs.nlp.annotators.resolution
SentenceEntityResolverModel
Companion class SentenceEntityResolverModel
object SentenceEntityResolverModel extends ReadablePretrainedSentenceEntityResolver with Serializable
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- SentenceEntityResolverModel
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- Serializable
- ReadablePretrainedSentenceEntityResolver
- EvalEntityResolver
- HasPretrained
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def
accuracy(dataset: DataFrame, trueCol: String, resolverCol: String, numOfChars: Int = 0): Double
calculates the accuracy metric for the EntityResolverModel in the provided dataset; the dataset should contain a column with the true code and a column from the EntityResolverModel annotator
calculates the accuracy metric for the EntityResolverModel in the provided dataset; the dataset should contain a column with the true code and a column from the EntityResolverModel annotator
- dataset
Transformed DataFrame
- trueCol
Column with the ground truth code
- resolverCol
Column with the EntityResolverModel annotation
- returns
The rate of correct entities
- Definition Classes
- EvalEntityResolver
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def
addReader(reader: (SentenceEntityResolverModel, String, SparkSession) ⇒ Unit): Unit
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asInstanceOf[T0]: T0
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val
defaultLang: String
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- HasPretrained
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lazy val
defaultLoc: String
- Definition Classes
- ReadablePretrainedSentenceEntityResolver → HasPretrained
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val
defaultModelName: Some[String]
- Definition Classes
- ReadablePretrainedSentenceEntityResolver → HasPretrained
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def
hitsAtK(dataset: DataFrame, trueCol: String, resolverCol: String, k: Int, numOfChars: Int = 0): Double
- dataset
Transformed DataFrame
- trueCol
Column with the ground truth code
- resolverCol
Column with the EntityResolverModel annotation
- k
Number of results to include in the set (k parameter for Hits@K)
- numOfChars
Number of characters to compare from the codes starting from left; defaults to 0 which compares the full code
- returns
The rate of correct entities appearing in the top k entries for each instance list
- Definition Classes
- EvalEntityResolver
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final
def
isInstanceOf[T0]: Boolean
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def
load(path: String): SentenceEntityResolverModel
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notifyAll(): Unit
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def
pretrained(name: String, lang: String): SentenceEntityResolverModel
- Definition Classes
- ReadablePretrainedSentenceEntityResolver → HasPretrained
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def
pretrained(name: String): SentenceEntityResolverModel
- Definition Classes
- ReadablePretrainedSentenceEntityResolver → HasPretrained
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def
pretrained(): SentenceEntityResolverModel
- Definition Classes
- ReadablePretrainedSentenceEntityResolver → HasPretrained
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def
pretrained(name: String, lang: String, remoteLoc: String): SentenceEntityResolverModel
Java compliant-overrides
Java compliant-overrides
- Definition Classes
- ReadablePretrainedSentenceEntityResolver → HasPretrained
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def
read: MLReader[SentenceEntityResolverModel]
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- ParamsAndFeaturesReadable → DefaultParamsReadable → MLReadable
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