Triple

T6983315
Position Surface form Disambiguated ID Type / Status
Subject Murat district E161899 entity
Predicate namedAfter P63 FINISHED
Object Joachim Murat E89640 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: Joachim Murat | Statement: [Murat district, namedAfter, Joachim Murat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joachim Murat
Context triple: [Murat district, namedAfter, Joachim Murat]
  • A. Joachim Murat chosen
    Joachim Murat was a French cavalry commander and Marshal of the Empire under Napoleon who became King of Naples in the early 19th century.
  • B. Jean Murat
    Jean Murat was a French film actor known for his roles in early 20th-century cinema and his marriage to actress Annabella.
  • C. Pierre Bonaparte
    Pierre Bonaparte was a 19th-century French prince of the Bonaparte family, known for his controversial political involvement during the Second French Empire and for fatally shooting journalist Victor Noir.
  • D. Michel Ney
    Michel Ney was a prominent French military commander and marshal of the Napoleonic Wars, renowned for his bravery and leadership in major battles across Europe.
  • E. Jean-Andoche Junot
    Jean-Andoche Junot was a French general and close confidant of Napoleon Bonaparte, noted for his service in the Revolutionary and Napoleonic Wars, including major campaigns in Spain and Russia.
  • 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_69c68855dc0481909b4c7e9e9ed273db completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db90e9108190a7aedeef1fb17eb4 completed March 27, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761c671588190a4e7b5c26cdfe6ba completed March 28, 2026, 5:06 a.m.
Created at: March 27, 2026, 2:31 p.m.