Triple

T11535396
Position Surface form Disambiguated ID Type / Status
Subject Randhir Kapoor E273533 entity
Predicate sibling P363 FINISHED
Object Rajiv Kapoor E918497 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: Rajiv Kapoor | Statement: [Randhir Kapoor, sibling, Rajiv Kapoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rajiv Kapoor
Context triple: [Randhir Kapoor, sibling, Rajiv Kapoor]
  • A. Rajiv Kapoor chosen
    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. Deepak Kapur
    Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
  • C. Sanjay Kapoor
    Sanjay Kapoor is an Indian film and television actor and producer known for his work in Hindi cinema since the 1990s.
  • 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. Vikrant Kapoor
    Vikrant Kapoor is the central male protagonist in the 1999 Bollywood musical romance film "Taal," portrayed by actor Akshaye Khanna.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8839b4bb48190b748ec4119f36c11 completed April 10, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f60a4f804c81909abf5e9a88da1d91 completed May 2, 2026, 2:29 p.m.
Created at: April 8, 2026, 9:37 p.m.