Triple
T14446764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 100 Famous Japanese Mountains |
E358227
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Mount Nasu |
E445188
|
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 Nasu | Statement: [100 Famous Japanese Mountains, hasPart, Mount Nasu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Nasu Context triple: [100 Famous Japanese Mountains, hasPart, Mount Nasu]
-
A.
Mount Nasu
chosen
Mount Nasu is an active volcanic complex in Japan’s Tōhoku region, known for its geothermal activity, hiking trails, and scenic hot spring resorts.
-
B.
Mount Sankaku
Mount Sankaku is a small, popular hiking and viewpoint mountain located in Nishi-ku, Sapporo, Japan.
-
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 Sanpō
Mount Sanpō is a peak in Japan’s Chichibu mountain range, known for its forested hiking trails and scenic views of the surrounding interior ranges.
-
E.
Mount Naeba
Mount Naeba is a prominent volcanic peak in Japan’s Echigo Mountains, known for its ski resorts, hiking trails, and the former site of the Fuji Rock Festival.
- 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_69ffa11c81f481909129eef69e47d079 |
completed | May 9, 2026, 9:03 p.m. |
Created at: April 10, 2026, 1:19 a.m.