Triple

T1862498
Position Surface form Disambiguated ID Type / Status
Subject Robert Fraisse E34846 entity
Predicate workedOn P3 FINISHED
Object Ronin E207317 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: Ronin | Statement: [Robert Fraisse, workedOn, Ronin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ronin
Context triple: [Robert Fraisse, workedOn, Ronin]
  • A. Ronin chosen
    Ronin is a 1998 action thriller film directed by John Frankenheimer, best known for its intricate espionage plot and realistic, high-intensity car chases set in France.
  • B. 47 Ronin
    47 Ronin is a 2013 fantasy action film loosely inspired by the Japanese legend of the forty-seven rōnin, blending samurai drama with supernatural elements.
  • C. Katsuragi
    Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
  • D. Kyojin
    Kyojin is the popular nickname of the Yomiuri Giants, one of Japan’s most historic and successful professional baseball teams.
  • E. Den Kenjirō
    Den Kenjirō was a Japanese statesman and colonial administrator who served as Governor-General of Taiwan during the period of Japanese rule.
  • 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb09e714881909cef0f7e77b5b3b9 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaddc9188190bd49d6605fd0e812 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:34 p.m.