Triple
T3476404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ntlo ya Dikgosi |
E73386
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Gaborone |
E48971
|
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: Gaborone | Statement: [Ntlo ya Dikgosi, locatedIn, Gaborone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaborone Context triple: [Ntlo ya Dikgosi, locatedIn, Gaborone]
-
A.
Gaborone
chosen
Gaborone is the capital and largest city of Botswana, serving as its political and economic center.
-
B.
Maseru
Maseru is the largest city and administrative, economic, and cultural center of the Kingdom of Lesotho in southern Africa.
-
C.
Bulawayo
Bulawayo is Zimbabwe’s second-largest city and a major industrial, cultural, and transport hub in the southwestern part of the country.
-
D.
Tshwane
Tshwane is a major metropolitan area in South Africa that includes the country’s administrative capital, Pretoria, and serves as an important political and economic hub.
-
E.
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.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb5a5cb88190be5624ae224e4c91 |
completed | March 8, 2026, 6:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e4d1c7188190b0f98fdc51e6684a |
completed | March 14, 2026, 4:32 a.m. |
Created at: March 8, 2026, 3:17 p.m.