Triple

T11737457
Position Surface form Disambiguated ID Type / Status
Subject Michel Serres E279066 entity
Predicate placeOfDeath P21 FINISHED
Object Vincennes E138002 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: Vincennes | Statement: [Michel Serres, placeOfDeath, Vincennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vincennes
Context triple: [Michel Serres, placeOfDeath, Vincennes]
  • A. Vincennes chosen
    Vincennes is a historic commune just east of Paris, France, known for its medieval Château de Vincennes and long-standing royal connections.
  • B. Vincennes, Indiana
    Vincennes, Indiana is a historic city in southwestern Indiana known as the state’s oldest city and an early frontier settlement along the Wabash River.
  • C. Corydon
    Corydon is a controversial series of dialogues by André Gide that defends homosexuality by arguing for its naturalness and historical prevalence.
  • D. Lafayette, Indiana
    Lafayette, Indiana is a mid-sized city in northwestern Indiana known as a regional economic and educational hub near Purdue University.
  • E. Lafayette
    Lafayette is a mid-sized city in southern Louisiana known as a cultural hub of Cajun and Creole music, food, and festivals.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4ef1c4881909ad36dc27b1fe193 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019b318188190bfb7effcf42974d2 completed April 28, 2026, 2:21 a.m.
Created at: April 8, 2026, 9:41 p.m.