Triple
T11058947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huambo |
E261453
|
entity |
| Predicate | wasRenamed |
P3432
|
FINISHED |
| Object | Huambo |
E261453
|
NE FINISHED |
How this triple was built (2 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: Huambo | Statement: [Huambo, wasRenamed, Huambo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huambo Context triple: [Huambo, wasRenamed, Huambo]
-
A.
Huambo
chosen
Huambo is a major city in central Angola that served as a strategic stronghold and frequent battleground during the Angolan Civil War.
-
B.
Kasane
Kasane is a small town in northern Botswana that serves as a key gateway and service hub for visitors to Chobe National Park and the surrounding wildlife areas.
-
C.
Moanda
Moanda is a major mining town in southeastern Gabon known for its rich manganese deposits and role in the country’s extractive industry.
-
D.
Otjiwarongo
Otjiwarongo is a town in central Namibia known as a key commercial and transport hub for the surrounding agricultural and wildlife regions.
-
E.
Kapiri Mposhi
Kapiri Mposhi is a town in central Zambia that serves as a key rail and road junction linking the country to Tanzania and other regions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a4f3f88190a29710f64cef9d25 |
completed | April 9, 2026, 12:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c87ab0308190a6a6ada1708f0ec2 |
completed | April 18, 2026, 6:07 p.m. |
Created at: April 8, 2026, 9:26 p.m.