Triple
T16260600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ongwediva |
E394742
|
entity |
| Predicate | regionCapitalNearby |
P41518
|
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: [Ongwediva, regionCapitalNearby, Oshakati]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oshakati Context triple: [Ongwediva, regionCapitalNearby, Oshakati]
-
A.
Oshakati
chosen
Oshakati is a major northern Namibian town that serves as an important commercial and administrative hub.
-
B.
Yaunde
Yaunde is an alternative name for Kolo, likely referring to the same place or entity under a different local or historical designation.
-
C.
Kabanjahe
Kabanjahe is a principal town and administrative center in North Sumatra, Indonesia, known as a hub of Karo culture and gateway to the surrounding highland region.
-
D.
Mogoro
Mogoro is a small town and municipality in central-western Sardinia, Italy, known for its traditional crafts and wine production.
-
E.
Omuta
Omuta is an industrial city in southern Fukuoka Prefecture, Japan, historically known for its coal mining and chemical industries.
- 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_6a002d9de7548190974851dc54465f0b |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 5:04 a.m.