Triple

T24866751
Position Surface form Disambiguated ID Type / Status
Subject Spearman rank-order correlation coefficient E622306 entity
Predicate robustTo P67874 FINISHED
Object outliers in raw data LITERAL FINISHED

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: outliers in raw data | Statement: [Spearman rank-order correlation coefficient, robustTo, outliers in raw data]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: robustTo
Context triple: [Spearman rank-order correlation coefficient, robustTo, outliers in raw data]
  • A. isRobustVariantOf
    Indicates that one entity is a strengthened, more resilient, or more general form of another, preserving the original’s core properties while improving its robustness.
  • B. isResistant chosen
    Indicates that an entity can withstand, oppose, or is not significantly affected by a specified force, influence, or agent.
  • C. moreAdaptiveThan
    Indicates that one entity is better able to adjust or respond effectively to changes or varying conditions than another entity.
  • D. susceptibleTo
    Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
  • E. tolerates
    Indicates that one entity endures, accepts, or allows the presence, behavior, or condition of another entity without intervening to stop or change it.
  • F. None of above.

Provenance (3 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_69e2fac350d08190b3affde1b451a8c5 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f43043512481909501a3979cac9947 completed May 1, 2026, 4:46 a.m.
PD Predicate disambiguation batch_69f420fd375c81908ea4a4e60b76ee8f completed May 1, 2026, 3:41 a.m.
Created at: April 18, 2026, 5:22 a.m.