Triple
T17916850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matola River |
E447949
|
entity |
| Predicate | hasNameInPortuguese |
P1435
|
FINISHED |
| Object | Rio Matola |
E447949
|
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: Rio Matola | Statement: [Matola River, hasNameInPortuguese, Rio Matola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio Matola Context triple: [Matola River, hasNameInPortuguese, Rio Matola]
-
A.
Matola River
chosen
The Matola River is a waterway in southern Mozambique that flows into Maputo Bay near the capital, supporting local transport and port activities.
-
B.
Maputo River
Maputo River is a river in southern Africa that flows through Eswatini and Mozambique before emptying into the Indian Ocean near the city of Maputo.
-
C.
Mapusa River
Mapusa River is a coastal river in North Goa, India, that flows through the town of Mapusa and joins the Mandovi River before reaching the Arabian Sea.
-
D.
Mapocho River
The Mapocho River is a major waterway flowing through the city of Santiago, Chile, historically central to its development and urban landscape.
-
E.
Msunduzi River
The Msunduzi River is a river in South Africa’s KwaZulu-Natal province that forms part of the drainage system feeding into the Lake St Lucia estuarine complex.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a3062bfc819083f7c0521bad4db8 |
completed | April 19, 2026, 9:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03212c9e88819099fb04040e543d63 |
completed | May 12, 2026, 12:46 p.m. |
Created at: April 10, 2026, 10:20 a.m.