Triple

T2538507
Position Surface form Disambiguated ID Type / Status
Subject Gilles Deleuze E56326 entity
Predicate workLocation P7 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: [Gilles Deleuze, workLocation, Vincennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vincennes
Context triple: [Gilles Deleuze, workLocation, 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. Lafayette, Indiana
    Lafayette, Indiana is a mid-sized city in northwestern Indiana known as a regional economic and educational hub near Purdue University.
  • C. Lafayette
    Lafayette is a mid-sized city in southern Louisiana known as a cultural hub of Cajun and Creole music, food, and festivals.
  • D. Lafayette
    Lafayette was a French aristocrat and military officer who became a key general in the American Revolutionary War and a symbol of Franco-American alliance.
  • E. Mishawaka, Indiana
    Mishawaka, Indiana is a city in northern Indiana near South Bend, known for its manufacturing history and as the longtime base of vehicle maker AM General.
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd298fc2481908b2925bf6a06532b completed March 7, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5cfc54cc8190bb43b54f873ffa63 completed March 9, 2026, 11:51 p.m.
Created at: March 6, 2026, 9:47 p.m.