Triple

T1902504
Position Surface form Disambiguated ID Type / Status
Subject Abraham Wald E37720 entity
Predicate analyzed P170 FINISHED
Object survivorship bias in military aircraft damage 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: survivorship bias in military aircraft damage data | Statement: [Abraham Wald, analyzed, survivorship bias in military aircraft damage data]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: analyzed
Context triple: [Abraham Wald, analyzed, survivorship bias in military aircraft damage data]
  • A. analyzes chosen
    Indicates that one entity systematically examines or evaluates another entity to understand its nature, structure, or components.
  • B. helpsAnalyze
    Indicates that one entity assists another in examining, interpreting, or understanding something in a more detailed or effective way.
  • C. theorized
    Indicates that one entity has proposed or developed a theoretical explanation or hypothesis about another entity or phenomenon.
  • D. considered
    Indicates that one entity regards, judges, or thinks about another entity in a particular way or context.
  • E. concluded
    Indicates that an entity has brought an event, process, discussion, or agreement to an end, often after reaching a decision or final judgment.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb34d94fc8190a5bf1e582c77c725 completed March 7, 2026, 5:10 a.m.
PD Predicate disambiguation batch_69abafe9f8b0819086d8f6288511c66d completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:35 p.m.