Triple

T15065557
Position Surface form Disambiguated ID Type / Status
Subject Udyog Vihar E379745 entity
Predicate nearbyLandmark P350 FINISHED
Object Cyber City Gurugram E1135114 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: Cyber City Gurugram | Statement: [Udyog Vihar, nearbyLandmark, Cyber City Gurugram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cyber City Gurugram
Context triple: [Udyog Vihar, nearbyLandmark, Cyber City Gurugram]
  • A. Cyber City area of Gurugram chosen
    The Cyber City area of Gurugram is a major corporate and technology hub in the Delhi NCR region, known for its high-rise offices, multinational company campuses, and modern commercial infrastructure.
  • B. Cybercity Magarpatta
    Cybercity Magarpatta is the major IT and business hub within Magarpatta City in Pune, India, housing numerous technology companies and corporate offices.
  • C. Cyberabad
    Cyberabad is a popular moniker for the technology-driven, IT and software hub aspects of Hyderabad, India.
  • D. DLF Cyber Hub
    DLF Cyber Hub is a popular corporate, dining, and entertainment complex in Gurugram, India, known for its upscale restaurants, bars, and vibrant nightlife.
  • E. DLF Cyber Greens
    DLF Cyber Greens is a prominent commercial office complex in Gurugram’s Cyber City business district, housing numerous multinational corporations and technology companies.
  • 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_69d85cd7683881908d405c1b5d7b4f7f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dedeea750c819082d8823c9ab6c5a2 completed April 15, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69feae11d6648190bc9b5d4f520d694b completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:02 a.m.