Triple

T1678086
Position Surface form Disambiguated ID Type / Status
Subject Yesterday E36277 entity
Predicate starring P1507 FINISHED
Object Himesh Patel E144034 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: Himesh Patel | Statement: [Yesterday, starring, Himesh Patel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Himesh Patel
Context triple: [Yesterday, starring, Himesh Patel]
  • A. Himesh Patel chosen
    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."
  • B. Sacha Dhawan
    Sacha Dhawan is a British actor known for his versatile television and film roles, including his acclaimed portrayal of the Master in the long-running sci-fi series Doctor Who.
  • C. Dev Patel
    Dev Patel is a British actor known for his breakout role in "Slumdog Millionaire" and acclaimed performances in films such as "Lion" and "The Green Knight."
  • D. Ranbir Kapoor
    Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
  • E. Aamir Khan
    Aamir Khan is a renowned Indian film actor, director, and producer known for his critically acclaimed and socially impactful movies in Bollywood.
  • 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_69a886139ed081909af0940aa9313512 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa625f7e1081909c3c4fe76625783a completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71ba4db08190a532fb334fd0cd23 completed March 8, 2026, 12:55 p.m.
Created at: March 4, 2026, 7:29 p.m.