Triple

T21945173
Position Surface form Disambiguated ID Type / Status
Subject Border E541914 entity
Predicate castMember P1668 FINISHED
Object Avtar Gill 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: Avtar Gill | Statement: [Border, castMember, Avtar Gill]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avtar Gill
Context triple: [Border, castMember, Avtar Gill]
  • A. Avtar Gill chosen
    Avtar Gill is an Indian character actor known for his supporting roles in numerous Hindi films and television serials.
  • B. Baljeet Tjinder
    Baljeet Tjinder is a studious, academically driven boy in the animated series "Phineas and Ferb," known for his intelligence, anxiety about grades, and frequent involvement in the protagonists’ inventions and adventures.
  • C. Jimmy Sheirgill
    Jimmy Sheirgill is an Indian film actor and producer known for his work in Hindi and Punjabi cinema, often portraying intense and understated romantic or dramatic roles.
  • D. Karan Bhalla
    Karan Bhalla is a relatively obscure individual whose public notability appears limited or not well-documented.
  • E. Sathnam Sanghera
    Sathnam Sanghera is a British journalist and author known for his memoir "The Boy with the Topknot" and his writing on British Sikh identity, class, and the legacy of empire.
  • 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_69e0c47e2e5c81909a7f74ce3de50911 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1242688988190a7b8f033c49368de completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:56 p.m.