Triple

T413272
Position Surface form Disambiguated ID Type / Status
Subject Khyber Pakhtunkhwa E9536 entity
Predicate hasCity P316 FINISHED
Object Swabi
Swabi is a city in northern Pakistan known as an agricultural and commercial center in the Khyber Pakhtunkhwa province.
 E54838 NE FINISHED

How this triple was built (4 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: Swabi | Statement: [Khyber Pakhtunkhwa, hasCity, Swabi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Swabi
Context triple: [Khyber Pakhtunkhwa, hasCity, Swabi]
  • A. Mingora
    Mingora is the largest city in Pakistan’s Swat Valley, known as a commercial and tourist hub and as the hometown of Nobel laureate Malala Yousafzai.
  • B. Bannu
    Bannu is a historic city in northwestern Pakistan known as a regional commercial and cultural center in the Khyber Pakhtunkhwa province.
  • C. Dera Ismail Khan
    Dera Ismail Khan is a historic city in southern Khyber Pakhtunkhwa, Pakistan, situated near the Indus River and serving as an important regional administrative and commercial center.
  • D. Haripur
    Haripur is a city in northern Pakistan known as an administrative and commercial center in the Hazara region of Khyber Pakhtunkhwa.
  • E. Mansehra
    Mansehra is a major city in northern Pakistan known as a gateway to the Kaghan Valley and the Karakoram Highway.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Swabi
Triple: [Khyber Pakhtunkhwa, hasCity, Swabi]
Generated description
Swabi is a city in northern Pakistan known as an agricultural and commercial center in the Khyber Pakhtunkhwa province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Swabi
Target entity description: Swabi is a city in northern Pakistan known as an agricultural and commercial center in the Khyber Pakhtunkhwa province.
  • A. Mingora
    Mingora is the largest city in Pakistan’s Swat Valley, known as a commercial and tourist hub and as the hometown of Nobel laureate Malala Yousafzai.
  • B. Bannu
    Bannu is a historic city in northwestern Pakistan known as a regional commercial and cultural center in the Khyber Pakhtunkhwa province.
  • C. Dera Ismail Khan
    Dera Ismail Khan is a historic city in southern Khyber Pakhtunkhwa, Pakistan, situated near the Indus River and serving as an important regional administrative and commercial center.
  • D. Haripur
    Haripur is a city in northern Pakistan known as an administrative and commercial center in the Hazara region of Khyber Pakhtunkhwa.
  • E. Mansehra
    Mansehra is a major city in northern Pakistan known as a gateway to the Kaghan Valley and the Karakoram Highway.
  • F. None of above. chosen

Provenance (5 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ecdc422881908910428fd1aee7c6 completed Feb. 28, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a431dd98dc8190a0020cdbeec5cfbf completed March 1, 2026, 12:32 p.m.
NEDg Description generation batch_69a43267c1d081908b2036402ce0ec11 completed March 1, 2026, 12:34 p.m.
NED2 Entity disambiguation (via description) batch_69a432f94a948190a958bba70c2fc806 completed March 1, 2026, 12:37 p.m.
Created at: Feb. 28, 2026, 1:09 p.m.