Triple
T3957106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiso River |
E85808
|
entity |
| Predicate | riverSystem |
P1009
|
FINISHED |
| Object | Kiso River system |
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 system | Statement: [Kiso River, riverSystem, Kiso River system]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiso River system Context triple: [Kiso River, riverSystem, Kiso River system]
-
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.
Kizu River
The Kizu River is a significant river in Japan’s Kansai region that flows through Nara and Kyoto Prefectures before joining the Yodo River system.
-
C.
Yasu River
The Yasu River is a significant river in Japan’s Kansai region that flows through Shiga Prefecture and ultimately drains into Lake Biwa.
-
D.
Mikuma River
Mikuma River is a river in Ōita Prefecture, Japan, known for flowing through the city of Hita and for its traditional cormorant fishing and scenic riverside views.
-
E.
Naka River
Naka River is a river in Japan known for lending its name to the Imperial Japanese Navy light cruiser Naka.
- 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_69aed93a96908190bcbdbfa718f155bd |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef95bbb9c8190bd64c5b7ea2f341a |
completed | March 9, 2026, 4:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b533b1bd1c81909d901ee334cb7b31 |
completed | March 14, 2026, 10:08 a.m. |
Created at: March 9, 2026, 3:31 p.m.