Triple
T14069443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Route 136 |
E338563
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Kawazu |
—
|
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: Kawazu | Statement: [National Route 136, passesThrough, Kawazu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kawazu Context triple: [National Route 136, passesThrough, Kawazu]
-
A.
Kawazu
chosen
Kawazu is a small coastal town in Shizuoka Prefecture, Japan, known for its early-blooming Kawazu-zakura cherry blossoms and hot spring resorts.
-
B.
Takizawa
Takizawa is a city in northeastern Japan known for its rural landscapes and proximity to the regional center of Morioka in Iwate Prefecture.
-
C.
Urakawa
Urakawa is a coastal town in Hokkaido, Japan, known for its horse breeding industry and scenic Pacific shoreline.
-
D.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
-
E.
Nakagawa
Nakagawa is a river in Japan, likely a tributary or neighboring waterway associated with the Edogawa River system.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568d0404819087e0fe37c72162cb |
completed | April 14, 2026, 3 p.m. |
Created at: April 9, 2026, 10:21 p.m.