Triple
T3876339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oshana Region |
E92509
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Oshakati |
E397822
|
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: Oshakati | Statement: [Oshana Region, containsSettlement, Oshakati]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oshakati Context triple: [Oshana Region, containsSettlement, Oshakati]
-
A.
Oshakati
chosen
Oshakati is a major northern Namibian town that serves as an important commercial and administrative hub.
-
B.
Kadoma
Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
-
C.
Masindi
Masindi is a town in western Uganda that serves as a key gateway and service center for visitors to Murchison Falls National Park.
-
D.
Moshi
Moshi is a Tanzanian town in the Kilimanjaro Region that serves as a major gateway and base for climbers ascending Mount Kilimanjaro.
-
E.
Tabora
Tabora is a historic town in western Tanzania known as a regional trade center and former hub of 19th-century caravan routes.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec719c148190a731773ac262221b |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b52845684c8190b6f0676319a6fc3c |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:20 p.m.