Triple
T654876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gweru |
E11624
|
entity |
| Predicate | railConnectsTo |
P13914
|
FINISHED |
| Object | Maputo |
E70168
|
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: Maputo | Statement: [Gweru, railConnectsTo, Maputo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maputo Context triple: [Gweru, railConnectsTo, Maputo]
-
A.
Maputo
chosen
Maputo is the largest city and main economic and cultural center of Mozambique, located on the country’s southern coast along the Indian Ocean.
-
B.
Bulawayo
Bulawayo is Zimbabwe’s second-largest city and a major industrial, cultural, and transport hub in the southwestern part of the country.
-
C.
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.
-
D.
Durban
Durban is a major coastal city in South Africa known for its busy port, subtropical climate, and significant Indian community.
-
E.
Pietermaritzburg
Pietermaritzburg is a major city in South Africa’s KwaZulu-Natal province, historically significant as a colonial administrative center and now known for its Victorian architecture and role as a regional economic and educational hub.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a517ac148190aa032b77885bf709 |
completed | March 1, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a637452b0c8190a1e82989f20e68db |
completed | March 3, 2026, 1:20 a.m. |
Created at: March 1, 2026, 7:36 p.m.