Triple

T13804259
Position Surface form Disambiguated ID Type / Status
Subject Azamgarh district E331719 entity
Predicate hasVidhanSabhaConstituency P23217 FINISHED
Object Azamgarh E477965 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: Azamgarh | Statement: [Azamgarh district, hasVidhanSabhaConstituency, Azamgarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Azamgarh
Context triple: [Azamgarh district, hasVidhanSabhaConstituency, Azamgarh]
  • A. Azamgarh chosen
    Azamgarh is a city in the Purvanchal region of eastern Uttar Pradesh, India, known as an important cultural and educational center.
  • B. Amroha
    Amroha is a town and municipal board in Uttar Pradesh, India, known for its historical significance and cultural heritage.
  • C. Jaunpur
    Jaunpur is a historic city in the Indian state of Uttar Pradesh, known for its medieval architecture and cultural heritage.
  • D. Ghazipur
    Ghazipur is a city in the Indian state of Uttar Pradesh, known for its historical significance and as a regional hub in eastern Uttar Pradesh.
  • E. Hajipur
    Hajipur is a prominent city in the Indian state of Bihar, known as an important railway and commercial hub located near the state capital, Patna.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026c36108190a7436034a730a261 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcd08a3a1481908400e3e55bf38aac completed May 7, 2026, 5:48 p.m.
Created at: April 9, 2026, 10:12 p.m.