Triple
T17002773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 4 Squadron Air Force of Zimbabwe |
E412489
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Gweru |
E11624
|
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: Gweru | Statement: [No. 4 Squadron Air Force of Zimbabwe, location, Gweru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gweru Context triple: [No. 4 Squadron Air Force of Zimbabwe, location, Gweru]
-
A.
Gweru
chosen
Gweru is a central Zimbabwean city that serves as the capital of the Midlands Province and an important commercial and transportation hub.
-
B.
Gwaneum
Gwaneum is the Korean name for the bodhisattva of compassion, equivalent to Guanyin in Chinese and Kannon in Japanese Buddhist traditions.
-
C.
Goria
Goria is an Italian surname most notably associated with Giovanni Goria, a former Prime Minister of Italy.
-
D.
Gerede
Gerede is a town and district in Turkey known for its location in the mountainous Bolu region and its cold, snowy climate.
-
E.
Geira
Geira was a Wendish princess who became the first wife of Olaf Tryggvason, the future king of Norway.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d37f8ba88190b8d32a1d09b6e6fd |
completed | April 18, 2026, 6:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ece8730819084f4bbbd7579430c |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:32 a.m.