Triple
T18763201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Namibia |
E458826
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object | Kolmanskop |
—
|
NE NERFINISHED |
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: Kolmanskop | Statement: [Southern Namibia, hasAttraction, Kolmanskop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kolmanskop Context triple: [Southern Namibia, hasAttraction, Kolmanskop]
-
A.
Kolmanskop
chosen
Kolmanskop is a famous ghost town in Namibia’s Namib Desert, once a prosperous German colonial diamond mining settlement now known for its sand-filled, abandoned buildings.
-
B.
Hartebeesfontein
Hartebeesfontein is a small mining town in South Africa’s North West Province, historically associated with gold and uranium extraction.
-
C.
Karoi
Karoi is a small agricultural and commercial town in northern Zimbabwe known as a service center for the surrounding tobacco-growing region.
-
D.
Kraaifontein
Kraaifontein is a residential suburb in the northern outskirts of Cape Town, South Africa, known for its mixed urban and semi-rural character.
-
E.
Cornberg
Cornberg is a small municipality in the German state of Hesse, known for its rural setting and historical monastery complex.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d80a954819083946dafc0c7af05 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 10, 2026, 11:52 a.m.