Triple

T17960657
Position Surface form Disambiguated ID Type / Status
Subject Kings XI Punjab E449071 entity
Predicate owner P347 FINISHED
Object Preity Zinta NE NERFINISHED

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: Preity Zinta | Statement: [Kings XI Punjab, owner, Preity Zinta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Preity Zinta
Context triple: [Kings XI Punjab, owner, Preity Zinta]
  • A. Preity Zinta chosen
    Preity Zinta is an Indian film actress and entrepreneur best known for her work in Hindi cinema, including acclaimed performances in films like "Kal Ho Naa Ho," "Dil Chahta Hai," and "Veer-Zaara."
  • B. Neha Kapur
    Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
  • C. Kajol
    Kajol is a renowned Indian film actress celebrated for her powerful performances and iconic roles in Hindi cinema since the 1990s.
  • D. Lara Dutta
    Lara Dutta is an Indian actress, model, and former Miss Universe (2000) known for her work in Bollywood films.
  • E. Raveena Tandon
    Raveena Tandon is an Indian actress and producer known for her prominent roles in 1990s and early 2000s Bollywood films and for winning the National Film Award for Best Actress.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b131fa8481908cd756f350eb6359 completed April 19, 2026, 10:40 a.m.
Created at: April 10, 2026, 10:22 a.m.