Triple

T13661825
Position Surface form Disambiguated ID Type / Status
Subject Mau district E327015 entity
Predicate countrySubdivision P766 FINISHED
Object Uttar Pradesh E10722 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: Uttar Pradesh | Statement: [Mau district, countrySubdivision, Uttar Pradesh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uttar Pradesh
Context triple: [Mau district, countrySubdivision, Uttar Pradesh]
  • A. Uttar Pradesh chosen
    Uttar Pradesh is a populous northern Indian state known for its political influence, rich cultural and religious heritage, and historic cities such as Varanasi and Agra.
  • B. 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.
  • C. Haryana
    Haryana is a northern Indian state known for its significant agricultural output, rapid industrial growth, and proximity to the national capital, New Delhi.
  • D. Rajasthan
    Rajasthan is a northwestern Indian state known for its vast Thar Desert, historic Rajput forts and palaces, and rich cultural heritage.
  • E. Bihar
    Bihar is a populous state in eastern India known for its rich historical heritage, including ancient centers of learning like Nalanda and significant sites in Buddhist history.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc620df208190afaccf3ddd10aa60 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7942a29b88190acefc8b3b91d849f completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:52 p.m.