Triple

T28493737
Position Surface form Disambiguated ID Type / Status
Subject Gaston Doumergue (cenotaph) E721046 entity
Predicate honorsOfficeHeldByPerson P161674 FINISHED
Object President of France 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: President of France | Statement: [Gaston Doumergue (cenotaph), honorsOfficeHeldByPerson, President of France]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: honorsOfficeHeldByPerson
Context triple: [Gaston Doumergue (cenotaph), honorsOfficeHeldByPerson, President of France]
  • A. honorsOfficeHolder chosen
    Indicates that one entity formally recognizes or pays tribute to an individual who holds or has held a particular office or position.
  • 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. officeHolderOf
    Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
  • D. officeHoldersHaveRole
    Indicates that individuals or entities holding an office possess or are assigned a specific role associated with that office.
  • E. alsoHoldsOfficeOf
    Indicates that an entity currently holding one office or position simultaneously holds another office or position as well.
  • 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_69f01a5afdac8190ac6e72d5c100bd58 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f69edbb7648190bd89c57e0932eac1 completed May 3, 2026, 1:03 a.m.
PD Predicate disambiguation batch_69f69d17e8d48190b30bcc2f4bd81eb2 completed May 3, 2026, 12:55 a.m.
Created at: April 28, 2026, 3:03 a.m.