Triple

T8669323
Position Surface form Disambiguated ID Type / Status
Subject Jagdeep Dhankhar E205754 entity
Predicate stateOfOrigin P3743 FINISHED
Object Rajasthan E9756 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: Rajasthan | Statement: [Jagdeep Dhankhar, stateOfOrigin, Rajasthan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rajasthan
Context triple: [Jagdeep Dhankhar, stateOfOrigin, Rajasthan]
  • A. Rajasthan chosen
    Rajasthan is a northwestern Indian state known for its vast Thar Desert, historic Rajput forts and palaces, and rich cultural heritage.
  • B. Gujarat
    Gujarat is a western coastal state of India known for its significant role in trade and industry, rich cultural heritage, and historic cities such as Ahmedabad.
  • C. Jaipur State
    Jaipur State was a prominent princely state in pre-independence India, ruled by Rajput kings from the Kachwaha dynasty with its capital at the historic city of Jaipur.
  • D. Chhattisgarh
    Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
  • E. Madhya Pradesh
    Madhya Pradesh is a large central Indian state known for its historical cities, diverse tribal cultures, and significant forested and wildlife areas including several major national parks.
  • 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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4917cb9881909a73b74e54250613 completed March 31, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ceccdaad2881908f131ee9da2841d1 completed April 2, 2026, 8:08 p.m.
Created at: March 30, 2026, 6:31 p.m.