Triple

T4168082
Position Surface form Disambiguated ID Type / Status
Subject Kinky Boots E84491 entity
Predicate leadCharacter P1668 FINISHED
Object Don E75078 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: Don | Statement: [Kinky Boots, leadCharacter, Don]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don
Context triple: [Kinky Boots, leadCharacter, Don]
  • A. Don
    The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • B. Don chosen
    Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
  • C. Danny
    Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
  • D. Danny
    Danny is the charismatic, hard-drinking World War I veteran whose inherited houses and loose community of friends drive the picaresque adventures in John Steinbeck’s novel "Tortilla Flat."
  • E. Dave
    Dave is a common masculine given name, often a shortened form of David, used widely in English-speaking countries.
  • 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_69aed932cab48190b80ffe35f7029ae1 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02c573788190a60ab3f83b07a6f6 completed March 9, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f4c2c988190959496cc0cc31cac completed March 14, 2026, 3:31 p.m.
Created at: March 9, 2026, 3:44 p.m.