Triple

T2684641
Position Surface form Disambiguated ID Type / Status
Subject Bannu Division E57454 entity
Predicate capital P234 FINISHED
Object Bannu E54094 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: Bannu | Statement: [Bannu Division, capital, Bannu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bannu
Context triple: [Bannu Division, capital, Bannu]
  • A. Bannu chosen
    Bannu is a historic city in northwestern Pakistan known as a regional commercial and cultural center in the Khyber Pakhtunkhwa province.
  • B. Attock
    Attock is a historic city in northern Pakistan strategically located along the Indus River, long serving as a key gateway between the Punjab region and Khyber Pakhtunkhwa.
  • C. Chakwal Potohari
    Chakwal Potohari is a regional dialect of the Potohari language spoken primarily in and around the Chakwal district of Pakistan’s Punjab province.
  • D. Swabi
    Swabi is a city in northern Pakistan known as an agricultural and commercial center in the Khyber Pakhtunkhwa province.
  • E. Chakwal
    Chakwal is a city in Pakistan’s Punjab province, known as a regional administrative and commercial center in the Potohar Plateau 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9edba5c8190b86d6cba0f1964e2 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa0700d548190944544495a2d42f6 completed March 10, 2026, 4:39 a.m.
Created at: March 6, 2026, 9:54 p.m.