Triple

T16527705
Position Surface form Disambiguated ID Type / Status
Subject Jaideep Ahlawat E401482 entity
Predicate appearedIn P795 FINISHED
Object Gangs of Wasseypur E1218691 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: Gangs of Wasseypur | Statement: [Jaideep Ahlawat, appearedIn, Gangs of Wasseypur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gangs of Wasseypur
Context triple: [Jaideep Ahlawat, appearedIn, Gangs of Wasseypur]
  • A. Gangs of Wasseypur chosen
    Gangs of Wasseypur is a critically acclaimed Indian crime film saga directed by Anurag Kashyap, known for its gritty portrayal of coal mafia feuds and generational gang warfare in the town of Wasseypur.
  • B. Badlapur
    Badlapur is a rapidly developing suburban city in Maharashtra, India, known for its residential growth and rail connectivity to Mumbai.
  • C. Badlapur
    Badlapur is a town and administrative block in Uttar Pradesh, India, known for its local markets and role as a regional hub within Jaunpur district.
  • D. Badlapur
    Badlapur is a 2015 Indian neo-noir revenge thriller film directed by Sriram Raghavan, known for its dark tone, morally complex characters, and acclaimed performances.
  • E. Mirzapur
    Mirzapur is a city in the Indian state of Uttar Pradesh, known for its carpet and brassware industries and its location on the banks of the Ganges River.
  • 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed4b8a08190b5f179fc583001a6 completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067a7616c8190af486bef3331e115 completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:14 a.m.