Triple
T19147129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ou Mountains |
E468708
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Mount Iwate |
—
|
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: Mount Iwate | Statement: [Ou Mountains, contains, Mount Iwate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Iwate Context triple: [Ou Mountains, contains, Mount Iwate]
-
A.
Mount Iwate
chosen
Mount Iwate is a prominent stratovolcano in Japan’s Tōhoku region, known for its symmetrical cone, scenic hiking routes, and status as the highest peak in Iwate Prefecture.
-
B.
Mount Iide
Mount Iide is a prominent peak in Japan’s Iide Mountain Range, renowned for its rugged alpine scenery and popular hiking routes.
-
C.
Mount Hakkoda
Mount Hakkoda is a volcanic mountain complex in northern Honshu, Japan, known for its heavy snowfall, scenic hiking, and tragic 1902 military snowstorm disaster.
-
D.
Mount Hakodate
Mount Hakodate is a scenic mountain in Hakodate, Japan, famous for its panoramic night views over the city and harbor.
-
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 (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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e97a79a48190b243553023bf9081 |
completed | April 20, 2026, 8:53 a.m. |
Created at: April 10, 2026, 12:06 p.m.