Triple

T11792391
Position Surface form Disambiguated ID Type / Status
Subject Pankaj Kapur E280419 entity
Predicate birthName P65 FINISHED
Object Pankaj Kapoor E280419 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: Pankaj Kapoor | Statement: [Pankaj Kapur, birthName, Pankaj Kapoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pankaj Kapoor
Context triple: [Pankaj Kapur, birthName, Pankaj Kapoor]
  • A. Rajiv Kapoor
    Rajiv Kapoor was an Indian film actor, director, and producer from the Kapoor family, known for starring in the 1985 film "Ram Teri Ganga Maili."
  • B. Sanjay Kapoor
    Sanjay Kapoor is an Indian film and television actor and producer known for his work in Hindi cinema since the 1990s.
  • C. Deepak Kapur
    Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
  • D. 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.
  • E. Pankaj Kapur chosen
    Pankaj Kapur is an acclaimed Indian actor and director known for his powerful performances in film, television, and theatre.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a588d2c881909783c2d678c2a474 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f63eda009481909870bd38200dd187 completed May 2, 2026, 6:13 p.m.
Created at: April 8, 2026, 9:42 p.m.