Triple
T3578441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koshi River |
E75742
|
entity |
| Predicate | formedByConfluenceOf |
P402
|
FINISHED |
| Object | Sun Koshi |
E370117
|
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: Sun Koshi | Statement: [Koshi River, formedByConfluenceOf, Sun Koshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sun Koshi Context triple: [Koshi River, formedByConfluenceOf, Sun Koshi]
-
A.
Sun Koshi
chosen
Sun Koshi is a significant Himalayan river in Nepal known for its long, challenging whitewater rafting routes and contribution to the Koshi river system.
-
B.
Yasu
Yasu is a Japanese city located in Shiga Prefecture, known for its blend of residential areas, local industry, and proximity to Lake Biwa.
-
C.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
-
D.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
E.
Kashin
Kashin is a historic town in western Russia known for its medieval heritage and location along the Kashinka River.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0defe14819095a337a840e33300 |
completed | March 8, 2026, 6:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b43301c2d8819089ee18732c1df29d |
completed | March 13, 2026, 3:53 p.m. |
Created at: March 8, 2026, 3:21 p.m.