Triple

T19688125
Position Surface form Disambiguated ID Type / Status
Subject Tau E472765 entity
Predicate usedAsSymbolFor P9907 FINISHED
Object Kendall rank correlation coefficient
The Kendall rank correlation coefficient is a nonparametric statistic that measures the strength and direction of association between two variables based on the concordance of their ranked data.
 E1390446 NE FINISHED

How this triple was built (4 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: Kendall rank correlation coefficient | Statement: [Tau, usedAsSymbolFor, Kendall rank correlation coefficient]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kendall rank correlation coefficient
Context triple: [Tau, usedAsSymbolFor, Kendall rank correlation coefficient]
  • A. Spearman rank-order correlation coefficient
    The Spearman rank-order correlation coefficient is a nonparametric statistical measure that assesses the strength and direction of a monotonic relationship between two ranked variables.
  • B. Kruskal–Goodman measures of association
    Kruskal–Goodman measures of association are nonparametric statistics used to quantify the strength and direction of association between ordinal variables.
  • C. Pearson correlation coefficient
    The Pearson correlation coefficient is a statistical measure that quantifies the strength and direction of the linear relationship between two continuous variables.
  • D. Bhattacharyya coefficient
    The Bhattacharyya coefficient is a statistical measure of similarity between two probability distributions, often used to quantify their overlap in fields like pattern recognition and signal processing.
  • E. Kruskal–Wallis test
    The Kruskal–Wallis test is a nonparametric statistical method used to determine whether there are statistically significant differences between the medians of three or more independent groups.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kendall rank correlation coefficient
Triple: [Tau, usedAsSymbolFor, Kendall rank correlation coefficient]
Generated description
The Kendall rank correlation coefficient is a nonparametric statistic that measures the strength and direction of association between two variables based on the concordance of their ranked data.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kendall rank correlation coefficient
Target entity description: The Kendall rank correlation coefficient is a nonparametric statistic that measures the strength and direction of association between two variables based on the concordance of their ranked data.
  • A. Spearman rank-order correlation coefficient
    The Spearman rank-order correlation coefficient is a nonparametric statistical measure that assesses the strength and direction of a monotonic relationship between two ranked variables.
  • B. Kruskal–Goodman measures of association
    Kruskal–Goodman measures of association are nonparametric statistics used to quantify the strength and direction of association between ordinal variables.
  • C. Pearson correlation coefficient
    The Pearson correlation coefficient is a statistical measure that quantifies the strength and direction of the linear relationship between two continuous variables.
  • D. Bhattacharyya coefficient
    The Bhattacharyya coefficient is a statistical measure of similarity between two probability distributions, often used to quantify their overlap in fields like pattern recognition and signal processing.
  • E. Kruskal–Wallis test
    The Kruskal–Wallis test is a nonparametric statistical method used to determine whether there are statistically significant differences between the medians of three or more independent groups.
  • F. None of above. chosen

Provenance (5 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6420d39688190ad3a84dbffce4ffe completed April 20, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0787cb199c8190ac46595fab1fadf1 completed May 15, 2026, 8:53 p.m.
NEDg Description generation batch_6a0788f2a2a88190abeb32e0f1b76702 completed May 15, 2026, 8:58 p.m.
NED2 Entity disambiguation (via description) batch_6a0789e3e1d48190a2f643a997e7ff02 completed May 15, 2026, 9:02 p.m.
Created at: April 10, 2026, 1:45 p.m.