Triple
T1302613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matabeleland North |
E27799
|
entity |
| Predicate | hasTouristDestination |
P6629
|
FINISHED |
| Object |
Hwange town
Hwange town is a settlement in western Zimbabwe best known as a gateway to the nearby Hwange National Park and its wildlife tourism.
|
E152056
|
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: Hwange town | Statement: [Matabeleland North, hasTouristDestination, Hwange town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hwange town Context triple: [Matabeleland North, hasTouristDestination, Hwange town]
-
A.
Hwange National Park
Hwange National Park is Zimbabwe’s largest and oldest national park, renowned for its vast elephant populations and diverse wildlife-rich savanna landscapes.
-
B.
Victoria Falls town
Victoria Falls town is a major Zimbabwean resort town and gateway for visitors to the famous Victoria Falls on the Zambezi River.
-
C.
Gwanda
Gwanda is a small Zimbabwean town that serves as an administrative and commercial hub in the country’s arid south, known historically for cattle ranching and gold mining.
-
D.
Makhuwa
Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
-
E.
Mbabane
Mbabane is the largest city and administrative center of Eswatini, located in the country's western highlands.
- 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: Hwange town Triple: [Matabeleland North, hasTouristDestination, Hwange town]
Generated description
Hwange town is a settlement in western Zimbabwe best known as a gateway to the nearby Hwange National Park and its wildlife tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hwange town Target entity description: Hwange town is a settlement in western Zimbabwe best known as a gateway to the nearby Hwange National Park and its wildlife tourism.
-
A.
Hwange National Park
Hwange National Park is Zimbabwe’s largest and oldest national park, renowned for its vast elephant populations and diverse wildlife-rich savanna landscapes.
-
B.
Victoria Falls town
Victoria Falls town is a major Zimbabwean resort town and gateway for visitors to the famous Victoria Falls on the Zambezi River.
-
C.
Gwanda
Gwanda is a small Zimbabwean town that serves as an administrative and commercial hub in the country’s arid south, known historically for cattle ranching and gold mining.
-
D.
Makhuwa
Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
-
E.
Mbabane
Mbabane is the largest city and administrative center of Eswatini, located in the country's western highlands.
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c115ba64819081c55fa6807e19ef |
completed | March 1, 2026, 10:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbf27639081908bd91bb904a58d32 |
completed | March 8, 2026, 12:13 a.m. |
| NEDg | Description generation | batch_69acbf94e6e881908d15b2ef99f17668 |
completed | March 8, 2026, 12:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acc0b212608190bbb2310402d86ed9 |
completed | March 8, 2026, 12:20 a.m. |
Created at: March 1, 2026, 7:51 p.m.