Triple
T16802353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Annupuri |
E408388
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Niseko Town |
E83888
|
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: Niseko Town | Statement: [Mount Annupuri, locatedIn, Niseko Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niseko Town Context triple: [Mount Annupuri, locatedIn, Niseko Town]
-
A.
Niseko
chosen
Niseko is a renowned ski resort area in northern Japan famous for its abundant light powder snow, extensive slopes, and vibrant international winter sports scene.
-
B.
Yuzawa
Yuzawa is a Japanese city best known for its hot springs and ski resorts, making it a popular winter tourism destination.
-
C.
Tōyako
Tōyako is a town in Hokkaido, Japan, known for its scenic Lake Tōya, hot spring resorts, and volcanic landscapes within Shikotsu-Toya National Park.
-
D.
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.
-
E.
Teshikaga town
Teshikaga town is a municipality in eastern Hokkaido, Japan, known for its volcanic landscapes, hot spring resorts, and scenic lakes such as Lake Mashu and Lake Kussharo.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2c8fe58819087d3b83635255c34 |
completed | April 18, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012327b68881908ad5f4e2fe03f56a |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 5:22 a.m.