Triple

T5778616
Position Surface form Disambiguated ID Type / Status
Subject Piscine Molitor Patel E127504 entity
Predicate portrayedBy P1507 FINISHED
Object Irrfan Khan E125488 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: Irrfan Khan | Statement: [Piscine Molitor Patel, portrayedBy, Irrfan Khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irrfan Khan
Context triple: [Piscine Molitor Patel, portrayedBy, Irrfan Khan]
  • A. Irrfan Khan chosen
    Irrfan Khan was a critically acclaimed Indian actor known for his powerful performances in both Bollywood and international films such as "The Namesake," "Slumdog Millionaire," and "Life of Pi."
  • B. Naseeruddin Shah
    Naseeruddin Shah is a renowned Indian actor and director celebrated for his powerful performances in parallel cinema as well as mainstream Bollywood films.
  • C. Sanjeev Bhaskar
    Sanjeev Bhaskar is a British comedian, actor, and writer best known for his work on the sketch show "Goodness Gracious Me" and the sitcom "The Kumars at No. 42."
  • D. Aamir Khan
    Aamir Khan is a renowned Indian film actor, director, and producer known for his critically acclaimed and socially impactful movies in Bollywood.
  • E. Himesh Patel
    Himesh Patel is a British actor best known for his breakout lead role in the film "Yesterday" and supporting performances in major productions like "Tenet" and the series "Station Eleven."
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029e107348190a03086f1cbfae0d3 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0980d833481908e69a80a63bbe256 completed March 23, 2026, 1:31 a.m.
Created at: March 22, 2026, 3:50 p.m.