Triple
T6186323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gifu |
E138068
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Kiso River |
E85808
|
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: Kiso River | Statement: [Gifu, hasRiver, Kiso River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiso River Context triple: [Gifu, hasRiver, Kiso River]
-
A.
Kiso River
chosen
The Kiso River is a major river in central Japan known for flowing through the Kiso Valley and contributing to the Nōbi Plain’s fertile landscape.
-
B.
Lukusashi River
The Lukusashi River is a significant tributary waterway in Zambia that feeds into the larger Luangwa River system.
-
C.
Akuta River
The Akuta River is a waterway located in Japan's Ibaraki Prefecture, contributing to the region's local drainage and landscape.
-
D.
Naka River
Naka River is a river in Japan known for lending its name to the Imperial Japanese Navy light cruiser Naka.
-
E.
Taiya River
The Taiya River is a glacially fed river in Southeast Alaska that flows through the historic Klondike Gold Rush region near Skagway before emptying into the Taiya Inlet.
- 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_69c008a8fd408190b7ec6e42934974a6 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0621671988190938dd16242a2e4d5 |
completed | March 22, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eec098348190a01ca8eca035592c |
completed | March 27, 2026, 8:55 p.m. |
Created at: March 22, 2026, 4:19 p.m.