Triple

T17520806
Position Surface form Disambiguated ID Type / Status
Subject Gaussian mixture model E426674 entity
Predicate basedOn P98 FINISHED
Object Gaussian distribution — NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gaussian distribution | Statement: [Gaussian mixture model, basedOn, Gaussian distribution]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gaussian distribution
Context triple: [Gaussian mixture model, basedOn, Gaussian distribution]
  • A. Gaussian distribution chosen
    The Gaussian distribution, also known as the normal distribution, is a fundamental continuous probability distribution characterized by its symmetric bell-shaped curve and central role in statistics and the natural sciences.
  • B. Gaussian
    Gaussian is a widely used computational chemistry software package that performs electronic structure calculations, including density functional theory, for molecules and materials.
  • C. Laplace distribution
    The Laplace distribution is a continuous probability distribution with a sharp peak at its mean and heavier tails than the normal distribution, often used to model data with abrupt changes or outliers.
  • D. Dirichlet distribution
    The Dirichlet distribution is a family of continuous multivariate probability distributions commonly used as a prior over categorical or multinomial parameters in Bayesian statistics.
  • E. Pearson distribution
    The Pearson distribution is a family of continuous probability distributions introduced by Karl Pearson to flexibly model data with varying skewness and kurtosis.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d23cf08190925510344fa36f57 completed April 19, 2026, 3:58 a.m.
Created at: April 10, 2026, 5:49 a.m.