Triple

T26593229
Position Surface form Disambiguated ID Type / Status
Subject Richard Nixon Foundation E667416 entity
Predicate namedAfterOfficeHeld P163721 FINISHED
Object 37th president of the United States 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: 37th president of the United States | Statement: [Richard Nixon Foundation, namedAfterOfficeHeld, 37th president of the United States]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: namedAfterOfficeHeld
Context triple: [Richard Nixon Foundation, namedAfterOfficeHeld, 37th president of the United States]
  • A. namedAfterOfficeholder chosen
    Indicates that one entity is named in honor of, or derived from the name of, a person who has held a particular public or official office.
  • B. possibleOfficeHeld
    Indicates that an entity may have held, or is a candidate to have held, a particular office or position, without asserting it as a confirmed fact.
  • C. lastOfficeHolderLaterBecame
    Indicates that the person who most recently held a given office subsequently went on to hold another specified office or role.
  • D. officePreviouslyHeldBy
    Indicates that a particular office or position was formerly occupied by a specified person or entity.
  • E. notableFormerOfficeHolderRole
    Indicates that an entity previously held a particular official position or role that is considered notable.
  • 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_69ee9cfc385081909ac9ae178030a06e completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f643ed0b7481908cf25f3afec0a61d completed May 2, 2026, 6:35 p.m.
PD Predicate disambiguation batch_69f641dc8ff48190ab575d855616580c completed May 2, 2026, 6:26 p.m.
Created at: April 27, 2026, 2:09 a.m.