Triple

T16528134
Position Surface form Disambiguated ID Type / Status
Subject Piyush Mishra E401491 entity
Predicate notableWork P4 FINISHED
Object Tamasha E102184 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: Tamasha | Statement: [Piyush Mishra, notableWork, Tamasha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamasha
Context triple: [Piyush Mishra, notableWork, Tamasha]
  • A. Tamasha chosen
    Tamasha is a traditional Marathi folk theatre form from Maharashtra, India, known for its lively blend of music, dance, and dramatic performance.
  • B. Mardaani
    Mardaani is a 2014 Indian crime thriller film that follows a tough female police officer’s pursuit of a child trafficking racket.
  • C. Bhagam Bhag
    Bhagam Bhag is a 2006 Indian Hindi-language comedy film directed by Priyadarshan, known for its slapstick humor and ensemble cast including Akshay Kumar, Govinda, and Lara Dutta.
  • D. Dilwaala
    Dilwaala is an Indian film best known for featuring actress Persis Khambatta in a notable role.
  • E. Humraaz
    Humraaz is a 2002 Hindi-language romantic thriller film directed by Abbas–Mustan, known for its twist-filled plot involving love, betrayal, and a high-stakes murder conspiracy.
  • 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_69e32ed57be481908625d4c5aab0940c completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00608efd0c81908e64419bd74eb285 completed May 10, 2026, 10:40 a.m.
Created at: April 10, 2026, 5:14 a.m.