Triple
T8534083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsuyama |
E202029
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Ishite River |
E793991
|
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: Ishite River | Statement: [Matsuyama, hasRiver, Ishite River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ishite River Context triple: [Matsuyama, hasRiver, Ishite River]
-
A.
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.
-
B.
Shigenobu River
chosen
Shigenobu River is a major river in Ehime Prefecture on Japan’s Shikoku Island, flowing through the city of Matsuyama and playing an important role in its landscape and water supply.
-
C.
Shirinashi River
Shirinashi River is a small urban waterway flowing through Naniwa-ku in Osaka, Japan.
-
D.
Shingashi River
The Shingashi River is a scenic waterway in Saitama Prefecture, Japan, known for flowing through the historic castle town of Kawagoe and its popular cherry blossom viewing spots.
-
E.
Warashina River
Warashina River is a regional river in Shizuoka Prefecture, Japan, that flows through Shizuoka City and contributes to its local watershed and landscape.
- 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_69ca832355b08190b8b6a4ab4a4a3554 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6a0ccd4819097b41d0dfb1c5018 |
completed | March 31, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d100a931988190aaff56f16057ea90 |
completed | April 4, 2026, 12:14 p.m. |
Created at: March 30, 2026, 6:17 p.m.