Triple

T7957237
Position Surface form Disambiguated ID Type / Status
Subject Kalyani E184770 entity
Predicate district P2709 FINISHED
Object Nadia district E164529 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: Nadia district | Statement: [Kalyani, district, Nadia district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nadia district
Context triple: [Kalyani, district, Nadia district]
  • A. Nadia district chosen
    Nadia district is an administrative district in the Indian state of West Bengal, known for its historical towns, cultural heritage, and agricultural economy.
  • B. Almaza district
    Almaza district is a neighborhood in eastern Cairo, Egypt, known for its residential areas, military facilities, and the historic Almaza Airport.
  • C. Badrashin district
    Badrashin district is an administrative region in Giza Governorate, Egypt, known for encompassing several important archaeological and historical sites near ancient Memphis.
  • D. Nazyan District
    Nazyan District is an administrative district in eastern Afghanistan known for its predominantly Pashtun population and location within Nangarhar Province near the Pakistan border.
  • E. Baabda District
    Baabda District is an administrative district in the Mount Lebanon Governorate of Lebanon that includes key suburbs of Beirut and has historically been a significant political and military area.
  • 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_69ca8292cba881908a64427b938dac47 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b7d36c081908cc8760a0dbf6001 completed March 31, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63b1dca08190926823fce1c0df6f completed April 1, 2026, 12:15 a.m.
Created at: March 30, 2026, 5:11 p.m.