Triple

T33058465
Position Surface form Disambiguated ID Type / Status
Subject Purdue University Aeronautical and Astronautical Engineering Alumni E845906 entity
Predicate employerTypical P28583 FINISHED
Object NASA NE NERFINISHED

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: NASA | Statement: [Purdue University Aeronautical and Astronautical Engineering Alumni, employerTypical, NASA]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: employerTypical
Context triple: [Purdue University Aeronautical and Astronautical Engineering Alumni, employerTypical, NASA]
  • A. typicalEmployer chosen
    Indicates that one entity is the kind of organization or person that commonly or usually employs the other entity.
  • B. employerType
    Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
  • C. typicalEmployerUnit
    Indicates that one entity is the standard or characteristic organizational unit that employs or is expected to employ another entity.
  • D. employerIn
    Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
  • E. employerInReality
    Indicates that one entity is the actual, real-world employer of another entity, as opposed to a nominal, legal, or assumed employer.
  • 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_69f3495333b8819095e9af56855b9061 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f7886be6d8819095ec62e4f2cee858 completed May 3, 2026, 5:39 p.m.
PD Predicate disambiguation batch_69f7841440f48190b4346c08855951d2 completed May 3, 2026, 5:21 p.m.
Created at: May 1, 2026, 1:25 a.m.