Triple
T1283867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mpumalanga |
E27387
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Sabie
Sabie is a small forestry and tourism town in northeastern South Africa, known as a gateway to waterfalls and scenic routes near the Drakensberg escarpment.
|
E153309
|
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: Sabie | Statement: [Mpumalanga, contains, Sabie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sabie Context triple: [Mpumalanga, contains, Sabie]
-
A.
Lusiana
Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
-
B.
Kasulu
Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of the Kigoma Region.
-
C.
Sodwana Bay
Sodwana Bay is a renowned coastal destination in South Africa famous for its rich marine biodiversity, coral reefs, and world-class scuba diving and snorkeling opportunities.
-
D.
The Mara
The Mara is a quick-service restaurant at Disney’s Animal Kingdom Lodge offering African-inspired and American dishes in a casual setting.
-
E.
Vaal Triangle
The Vaal Triangle is a major industrial and urban region in South Africa, centered around the Vaal River and known for its heavy manufacturing and petrochemical industries.
- 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: Sabie Triple: [Mpumalanga, contains, Sabie]
Generated description
Sabie is a small forestry and tourism town in northeastern South Africa, known as a gateway to waterfalls and scenic routes near the Drakensberg escarpment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sabie Target entity description: Sabie is a small forestry and tourism town in northeastern South Africa, known as a gateway to waterfalls and scenic routes near the Drakensberg escarpment.
-
A.
Lusiana
Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
-
B.
Kasulu
Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of the Kigoma Region.
-
C.
Sodwana Bay
Sodwana Bay is a renowned coastal destination in South Africa famous for its rich marine biodiversity, coral reefs, and world-class scuba diving and snorkeling opportunities.
-
D.
The Mara
The Mara is a quick-service restaurant at Disney’s Animal Kingdom Lodge offering African-inspired and American dishes in a casual setting.
-
E.
Vaal Triangle
The Vaal Triangle is a major industrial and urban region in South Africa, centered around the Vaal River and known for its heavy manufacturing and petrochemical industries.
- 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b599ac819096fca9ada294d939 |
completed | March 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc6209a388190b9f018b63120b28c |
completed | March 8, 2026, 12:43 a.m. |
| NEDg | Description generation | batch_69acc697fdc8819081b8e06981417064 |
completed | March 8, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acc722d8608190acbef82f180b75d1 |
completed | March 8, 2026, 12:47 a.m. |
Created at: March 1, 2026, 7:50 p.m.