Triple

T3848203
Position Surface form Disambiguated ID Type / Status
Subject Governor of Haryana E85224 entity
Predicate seat P75 FINISHED
Object Chandigarh E15653 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: Chandigarh | Statement: [Governor of Haryana, seat, Chandigarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chandigarh
Context triple: [Governor of Haryana, seat, Chandigarh]
  • A. Chandigarh chosen
    Chandigarh is a planned city in northern India, renowned for its modernist architecture and urban design largely conceived by the Swiss-French architect Le Corbusier.
  • B. Shimla
    Shimla is a popular hill station and the capital city of Himachal Pradesh, known for its colonial-era architecture and scenic Himalayan surroundings in northern India.
  • C. Ludhiana
    Ludhiana is a major industrial city in the Indian state of Punjab, known especially for its textile and hosiery manufacturing.
  • D. Jammu
    Jammu is a historically significant city and region in northern India, known as the winter capital of Jammu and Kashmir and a former stronghold of Dogra rulers.
  • E. Delhi
    Delhi is a major metropolitan region and the capital territory of India, known for its political significance, rich history, and diverse culture.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeebcc8a0481909c35161336bdfbf9 completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5122eb2708190b1aa9da233481015 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:19 p.m.