Triple

T14461221
Position Surface form Disambiguated ID Type / Status
Subject Priyanka Chopra Jonas E358587 entity
Predicate notableWork P4 FINISHED
Object Don E739212 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: [Priyanka Chopra Jonas, notableWork, Don]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don
Context triple: [Priyanka Chopra Jonas, notableWork, 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
    Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
  • C. Don chosen
    Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
  • D. Danny
    Danny is the central protagonist of the horror novel "The Keep," around whom the story’s supernatural and psychological conflicts revolve.
  • E. 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.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91abc1008190a19de4f8f0112c9d completed April 14, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d890be88190afe61dde0d1e75a8 completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:19 a.m.