Triple

T12207437
Position Surface form Disambiguated ID Type / Status
Subject Wasserstein GAN E290870 entity
Predicate basedOn P98 FINISHED
Object Earth Mover's distance
Earth Mover's distance is a measure of dissimilarity between two probability distributions, interpreted as the minimum “cost” of transforming one distribution into the other.
 E971750 NE FINISHED

Disambiguation candidates (2 decisions)

The exact options the model was shown at each disambiguation step, with the option it chose highlighted — the evidence behind this triple's disambiguated ids.

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Earth Mover's distance
Context triple: [Wasserstein GAN, basedOn, Earth Mover's distance]
  • A. Hellinger distance
    Hellinger distance is a statistical measure of dissimilarity between probability distributions, derived from the Euclidean distance between their square-root densities and widely used in probability theory and information geometry.
  • B. Bhattacharyya distance
    Bhattacharyya distance is a statistical measure of similarity between two probability distributions, often used in pattern recognition and classification to quantify their overlap.
  • C. Mahalanobis distance
    Mahalanobis distance is a multivariate measure of the distance between a point and a distribution (or between distributions) that accounts for correlations between variables via the covariance matrix.
  • D. Jensen–Shannon divergence
    Jensen–Shannon divergence is a symmetrized and smoothed measure of dissimilarity between probability distributions, widely used in information theory and machine learning.
  • E. Kolmogorov distance
    Kolmogorov distance is a statistical metric that measures the maximum difference between two cumulative distribution functions, commonly used to quantify convergence in distribution and in goodness-of-fit tests.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Earth Mover's distance
Target entity description: Earth Mover's distance is a measure of dissimilarity between two probability distributions, interpreted as the minimum “cost” of transforming one distribution into the other.
  • A. Hellinger distance
    Hellinger distance is a statistical measure of dissimilarity between probability distributions, derived from the Euclidean distance between their square-root densities and widely used in probability theory and information geometry.
  • B. Bhattacharyya distance
    Bhattacharyya distance is a statistical measure of similarity between two probability distributions, often used in pattern recognition and classification to quantify their overlap.
  • C. Mahalanobis distance
    Mahalanobis distance is a multivariate measure of the distance between a point and a distribution (or between distributions) that accounts for correlations between variables via the covariance matrix.
  • D. Jensen–Shannon divergence
    Jensen–Shannon divergence is a symmetrized and smoothed measure of dissimilarity between probability distributions, widely used in information theory and machine learning.
  • E. Kolmogorov distance
    Kolmogorov distance is a statistical metric that measures the maximum difference between two cumulative distribution functions, commonly used to quantify convergence in distribution and in goodness-of-fit tests.
  • F. None of above. chosen

Provenance (5 batches)

Stage Batch ID Job type Status
creating batch_69d6ab65923081909acfc61b7a612233 elicitation completed
NER batch_69d91c7d8f5c8190a46e9caa2a920fa9 ner completed
NED1 batch_69f60a9d2f0c81908352cd9f0167c6ab ned_source_triple completed
NED2 batch_69f60fe8c2ec8190af7c69dd17ea75fe ned_description completed
NEDg batch_69f60f2154c8819081f9cf6f51e5255b nedg completed
Created at: April 8, 2026, 9:51 p.m.