Triple

T2687665
Position Surface form Disambiguated ID Type / Status
Subject Grand Duchy of Berg E57522 entity
Predicate ruler P403 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: [Grand Duchy of Berg, ruler, Joachim Murat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joachim Murat
Context triple: [Grand Duchy of Berg, ruler, 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. 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.
  • D. 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.
  • E. Jérôme Bonaparte
    Jérôme Bonaparte was the youngest brother of Napoleon who became King of Westphalia and later served as a Marshal of France.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9f1ba3081909a349a2f30f8f9c9 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69b055bd41108190920b7397c16d15f5 completed March 10, 2026, 5:32 p.m.
Created at: March 6, 2026, 9:54 p.m.