Triple

T16685608
Position Surface form Disambiguated ID Type / Status
Subject Subhash Ghai E405454 entity
Predicate notableWork P4 FINISHED
Object Ram Lakhan E546213 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: Ram Lakhan | Statement: [Subhash Ghai, notableWork, Ram Lakhan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ram Lakhan
Context triple: [Subhash Ghai, notableWork, Ram Lakhan]
  • A. Ram Lakhan chosen
    Ram Lakhan is a popular 1989 Hindi masala film directed by Subhash Ghai, known for its blend of action, drama, and comedy and its ensemble cast including Anil Kapoor, Jackie Shroff, and Anupam Kher.
  • B. HAL Ajeet
    HAL Ajeet is an Indian light fighter aircraft developed by Hindustan Aeronautics Limited as an improved, license-built variant of the British Folland Gnat.
  • C. Raj Babbar
    Raj Babbar is an Indian film and television actor turned politician, known for his work in Hindi and Punjabi cinema and his long-standing association with the Indian National Congress.
  • D. Ram Baran
    Ram Baran is the given name of Ram Baran Yadav, the first president of Nepal.
  • E. Madan Babu
    Madan Babu is a computational biologist known for his influential work on gene regulation, protein networks, and systems biology.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea550c0819085bd36c44237a61a completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a43f6a08190913ca123a2377f95 completed May 10, 2026, 1:38 p.m.
Created at: April 10, 2026, 5:19 a.m.