Triple

T16527635
Position Surface form Disambiguated ID Type / Status
Subject Rajkummar Rao E401481 entity
Predicate placeOfBirth P1 FINISHED
Object Gurgaon E78440 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: Gurgaon | Statement: [Rajkummar Rao, placeOfBirth, Gurgaon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gurgaon
Context triple: [Rajkummar Rao, placeOfBirth, Gurgaon]
  • A. Gurugram chosen
    Gurugram is a major financial and technology hub in the Indian state of Haryana, known for its modern skyline, multinational corporate offices, and proximity to New Delhi.
  • B. Noida
    Noida is a major planned city and technology hub in the National Capital Region near Delhi, known for its modern infrastructure, IT parks, and residential developments.
  • C. Faridabad
    Faridabad is a major industrial city in northern India known for its manufacturing sector and its location within the National Capital Region near New Delhi.
  • D. Manesar
    Manesar is an industrial and residential township in Haryana, India, known for its manufacturing hubs and proximity to Gurgaon and Delhi.
  • E. Kharghar
    Kharghar is a rapidly developing residential and commercial node in Navi Mumbai, Maharashtra, known for its planned infrastructure and connectivity to Mumbai via the suburban railway network.
  • 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed4b8a08190b5f179fc583001a6 completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00a508505881909cb7582916ad037c completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:14 a.m.