Triple
T14446761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 100 Famous Japanese Mountains |
E358227
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Mount Zaō |
E434791
|
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 Zaō | Statement: [100 Famous Japanese Mountains, hasPart, Mount Zaō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Zaō Context triple: [100 Famous Japanese Mountains, hasPart, Mount Zaō]
-
A.
Mount Zao
chosen
Mount Zao is a prominent volcanic mountain range in northern Japan known for its ski resorts, hot springs, and the emerald-colored Okama crater lake.
-
B.
Mount Chōkai
Mount Chōkai is a prominent stratovolcano on the border of Akita and Yamagata Prefectures in northern Japan, known for its symmetrical shape and scenic alpine landscapes.
-
C.
Mount Suiro
Mount Suiro is the tallest mountain on Biliran Island in the Philippines, forming a prominent part of the island’s volcanic landscape.
-
D.
Mount Ohiri
Mount Ohiri is the highest peak on the French Polynesian island of Taha'a in the Society Islands archipelago.
-
E.
Mount Haruna
Mount Haruna is an active stratovolcano in Gunma Prefecture, Japan, known for its scenic caldera lake, hot springs, and popular hiking and sightseeing spots.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9160126c8190a2862a1a3dde1aff |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff90815b64819082715292f6088c74 |
completed | May 9, 2026, 7:52 p.m. |
Created at: April 10, 2026, 1:19 a.m.