Triple

T16420378
Position Surface form Disambiguated ID Type / Status
Subject DS Active Scan Suspension E398799 entity
Predicate targetCustomerBenefit P25020 FINISHED
Object “magic carpet” ride feeling 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: “magic carpet” ride feeling | Statement: [DS Active Scan Suspension, targetCustomerBenefit, “magic carpet” ride feeling]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: targetCustomerBenefit
Context triple: [DS Active Scan Suspension, targetCustomerBenefit, “magic carpet” ride feeling]
  • A. benefitAppliesTo
    Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
  • B. primaryBenefit chosen
    Indicates that one entity serves as the main or most important advantage, gain, or positive outcome associated with another entity.
  • C. relatedBenefit
    Indicates that one entity provides an advantage, gain, or positive outcome that is connected or attributable to another entity.
  • D. expectedBenefit
    Indicates the benefit or positive outcome that is anticipated to result from a particular action, decision, or relationship between entities.
  • E. benefitsAre
    Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328f5c1bc8190a679f35bd6c0bc97 completed April 18, 2026, 6:47 a.m.
PD Predicate disambiguation batch_69e22701d2288190bf8676050758f172 completed April 17, 2026, 12:26 p.m.
Created at: April 10, 2026, 5:09 a.m.