Triple
T11268976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kohat Campus |
E266760
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kohat |
E55857
|
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: Kohat | Statement: [Kohat Campus, locatedIn, Kohat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kohat Context triple: [Kohat Campus, locatedIn, Kohat]
-
A.
Kohat
chosen
Kohat is a historic city in northwestern Pakistan known for its strategic location, military cantonment, and role as a regional administrative and commercial center.
-
B.
Koh
Koh is a common Chinese surname found among various Chinese communities worldwide, including in Singapore and Malaysia.
-
C.
Koh
Koh is a Korean surname borne by various notable individuals across fields such as law, politics, and the arts.
-
D.
Kogarah
Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
-
E.
Koht
Koht is a Norwegian surname most notably associated with historian and politician Halvdan Koht.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e94f60d48190bc925c3cb88641a8 |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ccd52c20819093e03bba2fd359b7 |
completed | April 19, 2026, 12:38 p.m. |
Created at: April 8, 2026, 9:31 p.m.