Triple
T1697554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Tshwane Metropolitan Municipality |
E36692
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Soshanguve
Soshanguve is a large township in the northern part of the Gauteng province of South Africa, known for its diverse population and proximity to Pretoria.
|
E192104
|
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: Soshanguve | Statement: [City of Tshwane Metropolitan Municipality, contains, Soshanguve]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soshanguve Context triple: [City of Tshwane Metropolitan Municipality, contains, Soshanguve]
-
A.
Lomwe
Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
-
B.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
C.
Makhuwa
Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
-
D.
Nzega
Nzega is a town and district in western Tanzania that serves as an important commercial and transport hub within the Tabora Region.
-
E.
Mabalako
Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
- 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: Soshanguve Triple: [City of Tshwane Metropolitan Municipality, contains, Soshanguve]
Generated description
Soshanguve is a large township in the northern part of the Gauteng province of South Africa, known for its diverse population and proximity to Pretoria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Soshanguve Target entity description: Soshanguve is a large township in the northern part of the Gauteng province of South Africa, known for its diverse population and proximity to Pretoria.
-
A.
Lomwe
Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
-
B.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
C.
Makhuwa
Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
-
D.
Nzega
Nzega is a town and district in western Tanzania that serves as an important commercial and transport hub within the Tabora Region.
-
E.
Mabalako
Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
- 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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62b78d20819096f0602058c46d8a |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8ac9ed2c81909fe3fe40515526de |
completed | March 8, 2026, 2:42 p.m. |
| NEDg | Description generation | batch_69ad957778a0819080f7fee35f5d8ed5 |
completed | March 8, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad97aa308c81909f245a2133fc471b |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 4, 2026, 7:30 p.m.