Triple
T14813802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caledon River |
E348255
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Maseru |
E78539
|
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: Maseru | Statement: [Caledon River, passesNear, Maseru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maseru Context triple: [Caledon River, passesNear, Maseru]
-
A.
Maseru
chosen
Maseru is the largest city and administrative, economic, and cultural center of the Kingdom of Lesotho in southern Africa.
-
B.
Gaborone
Gaborone is the capital and largest city of Botswana, serving as its political and economic center.
-
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.
Gqeberha
Gqeberha is a major coastal city in South Africa’s Eastern Cape, known as an important industrial, commercial, and port hub.
-
E.
Manzini
Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe0e89c81908c0e1fe2bc3ebcfc |
completed | April 14, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24cca0b88190b20a6c7dd77b8146 |
completed | May 8, 2026, 6 p.m. |
Created at: April 10, 2026, 1:48 a.m.