Triple
T10383715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Alps |
E244705
|
entity |
| Predicate | hasPeakOver3000m |
P93893
|
FINISHED |
| Object | Mount Arakawa-Naka |
E879311
|
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: Mount Arakawa-Naka | Statement: [Southern Alps, hasPeakOver3000m, Mount Arakawa-Naka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Arakawa-Naka Context triple: [Southern Alps, hasPeakOver3000m, Mount Arakawa-Naka]
-
A.
Mount Arakawa-Naka
chosen
Mount Arakawa-Naka is a prominent peak in Japan’s Southern Alps, known for its rugged alpine terrain and challenging hiking routes.
-
B.
Mount Okura
Mount Okura is a hill in Sapporo, Japan, best known for its large ski jumping stadium and panoramic views over the city.
-
C.
Mount Atago
Mount Atago is a prominent mountain in Japan, revered for its Shinto shrines and historical significance as a site dedicated to the fire deity Atago Gongen.
-
D.
Mount Sankaku
Mount Sankaku is a small, popular hiking and viewpoint mountain located in Nishi-ku, Sapporo, Japan.
-
E.
Mount Akaishi
Mount Akaishi is one of Japan’s major high peaks, known for its rugged alpine terrain and scenic vistas within the country’s central mountain ranges.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fb99ef088190b64661b2f42c320e |
completed | April 7, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23b1c5e4c81909628c77b80805353 |
completed | April 17, 2026, 1:52 p.m. |
Created at: April 6, 2026, 12:04 p.m.