Triple
T13345995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Route 36 |
E317950
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Tomakomai |
—
|
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: Tomakomai | Statement: [National Route 36, passesThrough, Tomakomai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomakomai Context triple: [National Route 36, passesThrough, Tomakomai]
-
A.
Tomakomai
Tomakomai is an industrial port city on the southern coast of Hokkaido, Japan, known for its paper manufacturing, shipping, and ferry connections.
-
B.
Okachimachi
Okachimachi is a bustling commercial and shopping district in Tokyo known for its discount stores, jewelry shops, and proximity to Ueno.
-
C.
Tomakomai, Hokkaido
chosen
Tomakomai is an industrial port city in southern Hokkaido, Japan, known for its paper and chemical industries and as a transportation hub with ferry links to Honshu.
-
D.
Noshiro
Noshiro is a coastal city in northern Japan known for its port on the Sea of Japan and its forestry and basketball traditions.
-
E.
Kamaishi
Kamaishi is a coastal city in northeastern Japan known for its historic iron and steel industry and as a venue for the 2019 Rugby World Cup.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e89c65c819093f3bea11d6073c5 |
completed | April 11, 2026, 1:06 a.m. |
Created at: April 9, 2026, 9:31 p.m.