Triple
T10765953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Suburbs of Cape Town |
E253954
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kirstenhof |
E253959
|
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: Kirstenhof | Statement: [Southern Suburbs of Cape Town, contains, Kirstenhof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kirstenhof Context triple: [Southern Suburbs of Cape Town, contains, Kirstenhof]
-
A.
Kirstenhof
chosen
Kirstenhof is a residential suburb in Cape Town, South Africa, situated near the well-known Pollsmoor Prison complex.
-
B.
Kellenhusen
Kellenhusen is a seaside resort town on the Baltic Sea coast of northern Germany, known for its beaches and tourism.
-
C.
Heiderhof
Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
-
D.
Saalhof
Saalhof is a historic medieval building complex in Frankfurt am Main that forms part of the city’s museum landscape and reflects its architectural and urban history.
-
E.
Jagdhof
Jagdhof is a notable local landmark associated with the area of Linn, likely known for its historical or architectural significance.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d7322d3a9c81909e58f6064643b814 |
completed | April 9, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de235fe7748190ba004f889da389ff |
completed | April 14, 2026, 11:22 a.m. |
Created at: April 8, 2026, 9:16 p.m.