Triple

T18704036
Position Surface form Disambiguated ID Type / Status
Subject Leverage Consulting & Associates E457325 entity
Predicate operationalCover P132360 FINISHED
Object private consulting firm 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: private consulting firm | Statement: [Leverage Consulting & Associates, operationalCover, private consulting firm]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: operationalCover
Context triple: [Leverage Consulting & Associates, operationalCover, private consulting firm]
  • A. coverUpBy
    Indicates that one entity conceals, suppresses, or hides the actions, information, or wrongdoing associated with another entity.
  • B. providesCoverage
    Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
  • C. typicallyCovers
    Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
  • D. usedCover
    Indicates that one entity employed another entity as a protective or concealing cover in a given context.
  • E. surfaceCover
    Indicates that one entity forms the material or layer that covers the outer surface of another entity.
  • F. None of above. chosen

Provenance (4 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671597ac819093dbb53553130f1e completed April 19, 2026, 11:36 p.m.
PD Predicate disambiguation batch_69e478de85088190ba5f005f1d39f587 completed April 19, 2026, 6:40 a.m.
PDg Predicate description generation batch_69e484133ee48190a80f1889d79f34c9 completed April 19, 2026, 7:28 a.m.
Created at: April 10, 2026, 11:49 a.m.