Triple

T19911785
Position Surface form Disambiguated ID Type / Status
Subject Gurdaspur Lok Sabha constituency E478563 entity
Predicate notableFormerMP P14473 FINISHED
Object Vinod Khanna 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: Vinod Khanna | Statement: [Gurdaspur Lok Sabha constituency, notableFormerMP, Vinod Khanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vinod Khanna
Context triple: [Gurdaspur Lok Sabha constituency, notableFormerMP, Vinod Khanna]
  • A. Vinod Khanna chosen
    Vinod Khanna was a prominent Indian film actor and politician, known for his leading roles in Hindi cinema from the 1970s onward and later service as a Member of Parliament.
  • B. Vikas Khanna
    Vikas Khanna is an acclaimed Indian chef, restaurateur, cookbook author, and filmmaker known for his Michelin-starred cooking and appearances on culinary television shows.
  • C. Deepak Kapur
    Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
  • D. Robin Bhatt
    Robin Bhatt is an Indian screenwriter known for his work on numerous successful Bollywood films, particularly in the romance and drama genres.
  • E. Roopesh Parekh
    Roopesh Parekh is a television and film producer known for his work on the adaptation of Agatha Christie's "Ordeal by Innocence."
  • 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_69d8e520682081909892916424699bd5 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e659908ba88190ae0ee0fbfe4ddf64 completed April 20, 2026, 4:51 p.m.
Created at: April 10, 2026, 1:53 p.m.