Triple

T22442072
Position Surface form Disambiguated ID Type / Status
Subject Dev Anand E554776 entity
Predicate notableWork P4 FINISHED
Object Hum Dono NE NERFINISHED

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: Hum Dono | Statement: [Dev Anand, notableWork, Hum Dono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hum Dono
Context triple: [Dev Anand, notableWork, Hum Dono]
  • A. Hum Dono chosen
    Hum Dono is a 1961 Hindi film best known for its memorable music, philosophical themes, and Dev Anand’s dual role performance.
  • B. Hum Dekhenge
    "Hum Dekhenge" is a famous Urdu revolutionary poem by Faiz Ahmed Faiz that has become an enduring anthem of resistance and hope against oppression.
  • C. Kaise Mujhe
    "Kaise Mujhe" is a popular romantic Hindi song from the 2008 Bollywood film Ghajini, composed by A. R. Rahman and noted for its soulful melody and emotional lyrics.
  • D. Jo Haal Dil Ka
    "Jo Haal Dil Ka" is a romantic Hindi song from the acclaimed 1999 Bollywood film Sarfarosh, known for its melodious composition and emotional lyrics.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ae2f7608190b1c1e8bd12ca2162 completed April 29, 2026, 1:12 a.m.
Created at: April 16, 2026, 8:47 p.m.