Triple
T3213942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Flats |
E67345
|
entity |
| Predicate | administrativeAuthority |
P86
|
FINISHED |
| Object | City of Cape Town |
E24410
|
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: City of Cape Town | Statement: [Cape Flats, administrativeAuthority, City of Cape Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Cape Town Context triple: [Cape Flats, administrativeAuthority, City of Cape Town]
-
A.
Cape Town
chosen
Cape Town is a major coastal city in South Africa known for its iconic Table Mountain, diverse culture, and role as the country’s legislative capital.
-
B.
Hub City
Hub City is the nickname for Hagerstown, Maryland, reflecting its historical role as a major regional transportation and commercial center.
-
C.
Hub City
Hub City is a common nickname for Moncton, a major transportation and commercial center in New Brunswick, Canada.
-
D.
Hub City
Hub City is the nickname of Crestview, Florida, reflecting its role as a central crossroads and regional center in the Florida Panhandle.
-
E.
Muizenberg
Muizenberg is a seaside suburb of Cape Town, South Africa, known for its popular surfing beach and colorful Victorian beach huts.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaabd01d48190be0dc610b9987a25 |
completed | March 8, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2771204e0819086ae2838a368589a |
completed | March 12, 2026, 8:19 a.m. |
Created at: March 8, 2026, 3:07 p.m.