Triple
T14136056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copperbelt Province |
E350297
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object |
Luanshya
Luanshya is a mining town in Zambia known for its copper production and role in the country’s Copperbelt region.
|
E1081867
|
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: Luanshya | Statement: [Copperbelt Province, majorCity, Luanshya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luanshya Context triple: [Copperbelt Province, majorCity, Luanshya]
-
A.
Thabazimbi
Thabazimbi is a small mining town in South Africa’s Limpopo province, known for its iron ore industry and proximity to the scenic Marakele National Park.
-
B.
Thohoyandou
Thohoyandou is a town in South Africa’s Limpopo province that serves as an administrative, commercial, and educational hub for the surrounding region.
-
C.
Lomwe
Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
-
D.
Namwala
Namwala is a rural town in southern Zambia known as a center of Ila cattle-herding culture along the Kafue River floodplain.
-
E.
Vhavenda
Vhavenda are a Bantu-speaking ethnic group primarily inhabiting the northern part of South Africa’s Limpopo Province, known for their rich cultural traditions, distinctive music and dance, and historical Venda kingdom.
- 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: Luanshya Triple: [Copperbelt Province, majorCity, Luanshya]
Generated description
Luanshya is a mining town in Zambia known for its copper production and role in the country’s Copperbelt region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Luanshya Target entity description: Luanshya is a mining town in Zambia known for its copper production and role in the country’s Copperbelt region.
-
A.
Thabazimbi
Thabazimbi is a small mining town in South Africa’s Limpopo province, known for its iron ore industry and proximity to the scenic Marakele National Park.
-
B.
Thohoyandou
Thohoyandou is a town in South Africa’s Limpopo province that serves as an administrative, commercial, and educational hub for the surrounding region.
-
C.
Lomwe
Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
-
D.
Namwala
Namwala is a rural town in southern Zambia known as a center of Ila cattle-herding culture along the Kafue River floodplain.
-
E.
Vhavenda
Vhavenda are a Bantu-speaking ethnic group primarily inhabiting the northern part of South Africa’s Limpopo Province, known for their rich cultural traditions, distinctive music and dance, and historical Venda kingdom.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610fb86c81909eb26bf9c13696ca |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf14439c81908b2a9999a35cc346 |
completed | May 7, 2026, 6:51 p.m. |
| NEDg | Description generation | batch_69fce396360481909fe12fdee307d00d |
completed | May 7, 2026, 7:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fce3d07f048190833bd56b46a9f5fb |
completed | May 7, 2026, 7:11 p.m. |
Created at: April 10, 2026, 12:18 a.m.