Triple
T6219519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Court of Zimbabwe |
E139074
|
entity |
| Predicate | hasSeatIn |
P3522
|
FINISHED |
| Object | Bulawayo |
E9766
|
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: Bulawayo | Statement: [High Court of Zimbabwe, hasSeatIn, Bulawayo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bulawayo Context triple: [High Court of Zimbabwe, hasSeatIn, Bulawayo]
-
A.
Bulawayo
chosen
Bulawayo is Zimbabwe’s second-largest city and a major industrial, cultural, and transport hub in the southwestern part of the country.
-
B.
Manzini
Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
-
C.
Maputo
Maputo is the largest city and main economic and cultural center of Mozambique, located on the country’s southern coast along the Indian Ocean.
-
D.
Bloemfontein
Bloemfontein is a major South African city known as the seat of the country’s highest courts and one of its three national capitals.
-
E.
Marondera
Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
- 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_69c008aecb0c81909984b48f733ce8ae |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062bbb768819099402d367f124639 |
completed | March 22, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c603e5b3d48190b156be02008a8c12 |
completed | March 27, 2026, 4:13 a.m. |
Created at: March 22, 2026, 4:21 p.m.