Triple
T13950414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Volga |
E335505
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Mologa River |
E318423
|
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: Mologa River | Statement: [Upper Volga, hasTributary, Mologa River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mologa River Context triple: [Upper Volga, hasTributary, Mologa River]
-
A.
Mologa River
chosen
The Mologa River is a significant waterway in western Russia that flows through several regions before emptying into the Rybinsk Reservoir on the Volga River.
-
B.
Ulanga River
The Ulanga River is a fictional East African waterway famously depicted as the treacherous river route navigated in C.S. Forester’s novel and the classic film "The African Queen."
-
C.
Mbagathi River
Mbagathi River is a watercourse in Kenya that forms part of the southern boundary of Nairobi National Park and supports its wildlife and ecosystems.
-
D.
Ruganzu River
Ruganzu River is a waterway in Rwanda that flows through the capital city, Kigali.
-
E.
Galana River
The Galana River is a major waterway in southeastern Kenya that flows through Tsavo National Park, supporting diverse wildlife and ecosystems before emptying into 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e131c608190b4ffdbada24a3208 |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd19164481909c2f35fbebf6150e |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 9, 2026, 10:17 p.m.