Triple

T8340472
Position Surface form Disambiguated ID Type / Status
Subject Marbeuf E195896 entity
Predicate associatedWithRoleOf P75765 FINISHED
Object future 32nd 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: future 32nd president of the United States | Statement: [Marbeuf, associatedWithRoleOf, future 32nd president of the United States]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithRoleOf
Context triple: [Marbeuf, associatedWithRoleOf, future 32nd president of the United States]
  • A. associatedWithAssociation
    Indicates a relationship where an entity is linked or connected to a particular association or organization.
  • B. associatedWithCharacterRole
    Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
  • C. associatedWithRoleOfNameBearer chosen
    Indicates that an entity is connected to or involved with the specific role or function held by a designated name bearer.
  • D. associatedWithStationRole
    Indicates that an entity has a connection or involvement with a specific role or function at a station.
  • E. associatedWithMatch
    Indicates a relationship where an entity is linked or connected to a particular match or matching event.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fe8989481909b32d4bfd586372d completed March 31, 2026, 8:03 a.m.
PD Predicate disambiguation batch_69cb70c6d0ec8190acf273b0e007b51a completed March 31, 2026, 6:59 a.m.
Created at: March 30, 2026, 5:57 p.m.