Triple
T13433007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Route 37 |
E320158
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Tōyako Town |
E1040667
|
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: Tōyako Town | Statement: [National Route 37, connects, Tōyako Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tōyako Town Context triple: [National Route 37, connects, Tōyako Town]
-
A.
Tōyako
chosen
Tōyako is a town in Hokkaido, Japan, known for its scenic Lake Tōya, hot spring resorts, and volcanic landscapes within Shikotsu-Toya National Park.
-
B.
Minamisanriku Town
Minamisanriku Town is a coastal municipality in northeastern Japan known for being heavily affected by the 2011 Tōhoku earthquake and tsunami and its subsequent reconstruction efforts.
-
C.
Kutchan Town
Kutchan Town is a snowy resort town in Hokkaido, Japan, known for its proximity to the Niseko ski area and heavy winter snowfall.
-
D.
Toyako Town
Toyako Town is a lakeside town in Hokkaido, Japan, known for its scenic volcanic landscapes, hot springs, and outdoor recreation around Lake Tōya.
-
E.
Taku City
Taku City is a municipality in Saga Prefecture, Japan, known for its historic sites and traditional Japanese townscape.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaed41a5481908800033303224adb |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7461f44b08190802290db7a4e6a5e |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:40 p.m.