Triple

T1535628
Position Surface form Disambiguated ID Type / Status
Subject Charles IX of France E32542 entity
Predicate deathPlace 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: [Charles IX of France, deathPlace, Vincennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vincennes
Context triple: [Charles IX of France, deathPlace, 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 was a French aristocrat and military officer who became a key general in the American Revolutionary War and a symbol of Franco-American alliance.
  • D. 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.
  • E. Crown Point, Indiana
    Crown Point, Indiana is a historic city in northwest Indiana known for its classic courthouse square and role as the county’s governmental and commercial hub.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90828cdf08190aa404a0c11335c7b completed March 5, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad30942dc481908de85bd2ca30c0bd completed March 8, 2026, 8:17 a.m.
Created at: March 4, 2026, 7:26 p.m.