Triple
T16260618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ondangwa Airport |
E394743
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ondangwa |
E397823
|
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: Ondangwa | Statement: [Ondangwa Airport, locatedIn, Ondangwa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ondangwa Context triple: [Ondangwa Airport, locatedIn, Ondangwa]
-
A.
Ondangwa
chosen
Ondangwa is a town in northern Namibia that serves as an important commercial and transport hub for the surrounding Oshana Region.
-
B.
Bongwe
Bongwe is a dialect of the Duala language spoken by the Duala people of Cameroon.
-
C.
Namwala
Namwala is a rural town in southern Zambia known as a center of Ila cattle-herding culture along the Kafue River floodplain.
-
D.
Bolongongo
Bolongongo is a town and municipality located in Angola’s Cuanza Norte Province.
-
E.
Luanshya
Luanshya is a mining town in Zambia known for its copper production and role in the country’s Copperbelt region.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c3e5388190942b0237ab5d1f0f |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c48c5cc8190ba99154e99942316 |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:04 a.m.