Triple
T19967284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunyani River |
E479970
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Manyame River |
—
|
NE NERFINISHED |
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: Manyame River | Statement: [Hunyani River, alsoKnownAs, Manyame River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manyame River Context triple: [Hunyani River, alsoKnownAs, Manyame River]
-
A.
Manyame River
chosen
The Manyame River is a major river in northern Zimbabwe that flows near the capital city of Harare and feeds into Lake Manyame, an important water source for the region.
-
B.
Nyamiha River
The Nyamiha River is a small, historically significant waterway in Minsk, Belarus, now largely confined to underground culverts beneath the city.
-
C.
Kutima River
Kutima River is a lesser-known river that serves as a tributary within the Kirenga River basin in Russia’s Siberian region.
-
D.
Lumezi River
The Lumezi River is a tributary watercourse in eastern Zambia that feeds into the larger Luangwa River system.
-
E.
Ilimpeya River
The Ilimpeya River is a remote Siberian river in Russia that flows through the Krasnoyarsk Krai region and contributes to the vast Yenisei river basin.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc5e41881908c1e8867820f1c0c |
completed | April 20, 2026, 5 p.m. |
Created at: April 10, 2026, 1:54 p.m.