Triple

T1980525
Position Surface form Disambiguated ID Type / Status
Subject Annabella E43014 entity
Predicate marriagePartner P13 FINISHED
Object Jean Murat E234985 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: Jean Murat | Statement: [Annabella, marriagePartner, Jean Murat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean Murat
Context triple: [Annabella, marriagePartner, Jean Murat]
  • A. Jean Murat chosen
    Jean Murat was a French film actor known for his roles in early 20th-century cinema and his marriage to actress Annabella.
  • B. Joachim Murat
    Joachim Murat was a French cavalry commander and Marshal of the Empire under Napoleon who became King of Naples in the early 19th century.
  • 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. André Masséna
    André Masséna was a prominent French military commander and one of Napoleon Bonaparte’s most celebrated marshals, renowned for his strategic skill during the Revolutionary and Napoleonic Wars.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb7c87bc081908ed179d1ca94fa3b completed March 7, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5176d2f08190b3ebc53ea1def9be completed March 9, 2026, 4:49 a.m.
Created at: March 4, 2026, 7:37 p.m.