Triple

T11983175
Position Surface form Disambiguated ID Type / Status
Subject Belle E285208 entity
Predicate associatedWith P37 FINISHED
Object Gaston E231330 NE 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: Gaston | Statement: [Belle, associatedWith, Gaston]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaston
Context triple: [Belle, associatedWith, Gaston]
  • A. Gaston chosen
    Gaston is a masculine given name of French origin commonly used in Francophone countries and beyond.
  • B. Gaston, Count of Eu
    Gaston, Count of Eu was a French-born nobleman and military officer who became a prominent figure in Brazil’s imperial family through his marriage to Princess Isabel, the heir to the Brazilian throne.
  • C. Gaspard
    Gaspard is a French masculine given name historically borne by notable figures such as nobles, military leaders, and artists.
  • D. Bonhomme
    Bonhomme is the iconic snowman mascot and symbol of the Quebec Winter Carnival, known for his red cap, sash, and festive public appearances.
  • E. Régis
    Régis is a masculine given name of French origin, historically borne by notable figures such as the statesman Jean-Jacques-Régis de Cambacérès.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903973c848190aac871d6dfecc74b completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d0791348190a2f6c0e808af3aea completed May 1, 2026, 12:31 p.m.
Created at: April 8, 2026, 9:46 p.m.