Triple
T18535909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakagyō-ku |
E452964
|
entity |
| Predicate | traversedBy |
P225
|
FINISHED |
| Object | Kamo River |
—
|
NE NERFINISHED |
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: Kamo River | Statement: [Nakagyō-ku, traversedBy, Kamo River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamo River Context triple: [Nakagyō-ku, traversedBy, Kamo River]
-
A.
Kamo River
chosen
The Kamo River is a prominent river running through Kyoto, Japan, known for its scenic banks, seasonal cherry blossoms, and role as a central gathering place for locals and visitors.
-
B.
Kamogawa River
The Kamogawa River is a prominent river flowing through Kyoto, Japan, known for its scenic banks lined with traditional teahouses, restaurants, and popular walking paths.
-
C.
Midori River
The Midori River is a Japanese river in Kyushu that flows through Kumamoto Prefecture before emptying into the Ariake Sea.
-
D.
Yoshino River
The Yoshino River is one of Japan’s major rivers, renowned for its strong currents, hydroelectric dams, and scenic gorges as it flows across the island of Shikoku.
-
E.
Kaminagawa River
The Kaminagawa River is a waterway flowing through Yurihonjō in Akita Prefecture, Japan, contributing to the city's natural landscape and local ecosystem.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5340193588190ace2c09c6a94cf81 |
completed | April 19, 2026, 7:58 p.m. |
Created at: April 10, 2026, 11:37 a.m.