Triple

T433166
Position Surface form Disambiguated ID Type / Status
Subject Rajasthan E9756 entity
Predicate bordersState P224 FINISHED
Object Gujarat E15090 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: Gujarat | Statement: [Rajasthan, bordersState, Gujarat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gujarat
Context triple: [Rajasthan, bordersState, Gujarat]
  • A. Gujarat chosen
    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.
  • B. Maharashtra
    Maharashtra is a large and economically significant state in western India, known for its capital Mumbai, the country’s financial hub, and its rich cultural and historical heritage.
  • C. Rajasthan
    Rajasthan is a northwestern Indian state known for its vast Thar Desert, historic Rajput forts and palaces, and rich cultural heritage.
  • D. 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.
  • E. Chhattisgarh
    Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
  • 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ef084840819080653004b674cba8 completed Feb. 28, 2026, 1:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7bffe8a488190939b1a778db4f517 completed March 4, 2026, 5:15 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.