Triple

T1802742
Position Surface form Disambiguated ID Type / Status
Subject Tamil cinema E39755 entity
Predicate hasNotableActor P17435 FINISHED
Object Kamal Haasan E179101 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: Kamal Haasan | Statement: [Tamil cinema, hasNotableActor, Kamal Haasan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kamal Haasan
Context triple: [Tamil cinema, hasNotableActor, Kamal Haasan]
  • A. Kamal Hasan chosen
    Kamal Hasan is a renowned Indian film actor, director, and producer celebrated for his versatile performances across multiple Indian film industries, particularly Tamil cinema.
  • B. Chiranjeevi
    Chiranjeevi is a legendary Indian film actor and former politician, widely regarded as one of the biggest and most influential stars in Telugu cinema.
  • C. Rajinikanth
    Rajinikanth is an iconic Indian film actor and cultural phenomenon, best known for his charismatic performances and larger-than-life roles primarily in Tamil cinema.
  • D. Allu Aravind
    Allu Aravind is a prominent Indian film producer and distributor, best known for founding the production company Geetha Arts and producing numerous successful Telugu and Hindi films.
  • E. Mahesh Babu
    Mahesh Babu is a leading Indian actor and producer best known for his work in Telugu cinema, where he is celebrated for his charismatic screen presence and numerous blockbuster films.
  • 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_69a88632aa588190ba3978fde0db5bbd completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa659535448190b60cb4b0ad2972b6 completed March 6, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf5645808190a774d96cfe5c5e58 completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:32 p.m.