Triple
T12696027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bannu Airport |
E303335
|
entity |
| Predicate | locatedInCity |
P40
|
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 Airport, locatedInCity, Bannu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bannu Context triple: [Bannu Airport, locatedInCity, 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.
Risalpur
Risalpur is a town in Pakistan’s Khyber Pakhtunkhwa province known as a major military and air force training center.
-
C.
Turbat
Turbat is a major city in southern Balochistan, Pakistan, known as a commercial and cultural center of the Makran region.
-
D.
Amarkot
Amarkot is an alternative name for Umarkot, a historic town and district in the Sindh province of Pakistan known for its cultural and Mughal-era significance.
-
E.
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.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ebd17081909f983567e4b36533 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8c37eb08190a4c15cb50f84c341 |
completed | May 3, 2026, 2:53 a.m. |
Created at: April 9, 2026, 5:22 p.m.