Triple

T8503847
Position Surface form Disambiguated ID Type / Status
Subject Javed Akhtar E201285 entity
Predicate wroteScreenplayFor P15305 FINISHED
Object Zanjeer E670874 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: Zanjeer | Statement: [Javed Akhtar, wroteScreenplayFor, Zanjeer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zanjeer
Context triple: [Javed Akhtar, wroteScreenplayFor, Zanjeer]
  • A. Zanjeer chosen
    Zanjeer is a landmark 1973 Indian action film that transformed Amitabh Bachchan into Bollywood’s iconic “angry young man” and helped redefine the Hindi film hero archetype.
  • B. Jawan
    Jawan is a 2023 Indian action thriller film starring Shah Rukh Khan, known for its high-octane action, social themes, and massive box-office success.
  • C. Badal
    Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
  • D. Kaalpurush
    Kaalpurush is an acclaimed Bengali film by director Buddhadeb Dasgupta that explores memory, time, and human relationships through a poetic, surreal narrative.
  • E. Sholay
    Sholay is a landmark 1975 Indian action-adventure film widely regarded as one of the greatest and most influential movies in Hindi cinema history.
  • 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_69ca831fe47c8190b5c57b456d2aefa0 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe59d67d081908155a43b9b463fe3 completed March 31, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e26a3108190a48b00c2927be971 completed April 2, 2026, 11:08 a.m.
Created at: March 30, 2026, 6:14 p.m.