Triple

T3813170
Position Surface form Disambiguated ID Type / Status
Subject National Capital Region E93183 entity
Predicate containsCity P294 FINISHED
Object Bharatpur E62480 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: Bharatpur | Statement: [National Capital Region, containsCity, Bharatpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bharatpur
Context triple: [National Capital Region, containsCity, Bharatpur]
  • A. Bharatpur chosen
    Bharatpur is a historic city in eastern Rajasthan, India, known for the Keoladeo National Park, a UNESCO World Heritage-listed bird sanctuary.
  • B. Sawai Madhopur
    Sawai Madhopur is a town in Rajasthan, India, best known as the main gateway to the tiger-rich Ranthambore region and its historic fort.
  • C. Udaipur
    Udaipur is a historic city in India renowned for its lakes, palaces, and role as a former capital of the Mewar kingdom.
  • D. Udaipur
    Udaipur is a historic town in the Indian state of Tripura, known for its ancient temples and scenic lakes.
  • E. Chittorgarh
    Chittorgarh is a historic city in Rajasthan, India, renowned for its massive hilltop fort, tales of Rajput valor, and rich cultural traditions.
  • 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee8dd315481908bef595b56a4f0cb completed March 9, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503f549b0819088b64ddb3f38238f completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:16 p.m.