Triple
T6203715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waterberg region |
E138697
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object |
Bela-Bela
Bela-Bela is a South African town in Limpopo Province known for its natural hot mineral springs and tourism-focused resorts.
|
E582934
|
NE FINISHED |
How this triple was built (4 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: Bela-Bela | Statement: [Waterberg region, nearestCity, Bela-Bela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bela-Bela Context triple: [Waterberg region, nearestCity, Bela-Bela]
-
A.
Masandawana
Masandawana is the popular nickname of South African football club Mamelodi Sundowns F.C., one of the country’s most successful and widely supported teams.
-
B.
Griqualand West
Griqualand West was a 19th-century British colonial territory in southern Africa, centered on the diamond-rich area around Kimberley.
-
C.
Lobamba
Lobamba is the traditional and legislative capital of Eswatini, serving as the seat of the Swazi monarchy and key national institutions.
-
D.
Makhuwa
Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
-
E.
Hoedspruit
Hoedspruit is a small South African town near Kruger National Park, known as a gateway to wildlife reserves and scenic Lowveld attractions.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bela-Bela Triple: [Waterberg region, nearestCity, Bela-Bela]
Generated description
Bela-Bela is a South African town in Limpopo Province known for its natural hot mineral springs and tourism-focused resorts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bela-Bela Target entity description: Bela-Bela is a South African town in Limpopo Province known for its natural hot mineral springs and tourism-focused resorts.
-
A.
Masandawana
Masandawana is the popular nickname of South African football club Mamelodi Sundowns F.C., one of the country’s most successful and widely supported teams.
-
B.
Griqualand West
Griqualand West was a 19th-century British colonial territory in southern Africa, centered on the diamond-rich area around Kimberley.
-
C.
Lobamba
Lobamba is the traditional and legislative capital of Eswatini, serving as the seat of the Swazi monarchy and key national institutions.
-
D.
Makhuwa
Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
-
E.
Hoedspruit
Hoedspruit is a small South African town near Kruger National Park, known as a gateway to wildlife reserves and scenic Lowveld attractions.
- F. None of above. chosen
Provenance (5 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626c23f481909d2b5b0a75c2ffff |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c518f798d8819080f5dc1bb988b3df |
completed | March 26, 2026, 11:31 a.m. |
| NEDg | Description generation | batch_69c52cb4b888819087cc98ed57184ff9 |
completed | March 26, 2026, 12:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c5840fe7d481908d75f8572d117364 |
completed | March 26, 2026, 7:08 p.m. |
Created at: March 22, 2026, 4:20 p.m.