Triple
T21870289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Mountain Range |
E539982
|
entity |
| Predicate | highestPointName |
P210
|
FINISHED |
| Object | Mount Yu |
—
|
NE NERFINISHED |
How this triple was built (3 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 Yu | Statement: [Central Mountain Range, highestPointName, Mount Yu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Yu Context triple: [Central Mountain Range, highestPointName, Mount Yu]
-
A.
Mount Li
Mount Li is a mountain in Shaanxi Province, China, historically significant as the burial site of the First Qin Emperor and the location of the famed Terracotta Army.
-
B.
Mount Yi
Mount Yi is a notable mountain in Shandong Province, China, known for its scenic landscapes and cultural-historical significance.
-
C.
Mount Qi
Mount Qi is a historically significant mountain in Shaanxi, China, closely associated with the early Zhou dynasty and revered as the legendary burial site of King Wen of Zhou.
-
D.
Mount Shiun
Mount Shiun is a scenic mountain in Takamatsu, Japan, known as the forested backdrop to Ritsurin Garden and a popular spot for panoramic views over the city and Seto Inland Sea.
-
E.
Mount Jinba
Mount Jinba is a scenic mountain on the border of Tokyo and Kanagawa in Japan, popular for its hiking trails and panoramic views of the surrounding region, including Mount Fuji on clear days.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mount Yu Target entity description: Mount Yu is a prominent peak in Taiwan’s Central Mountain Range, renowned for its rugged alpine scenery and popularity among hikers and mountaineers.
-
A.
Mount Li
Mount Li is a mountain in Shaanxi Province, China, historically significant as the burial site of the First Qin Emperor and the location of the famed Terracotta Army.
-
B.
Mount Yi
Mount Yi is a notable mountain in Shandong Province, China, known for its scenic landscapes and cultural-historical significance.
-
C.
Mount Qi
Mount Qi is a historically significant mountain in Shaanxi, China, closely associated with the early Zhou dynasty and revered as the legendary burial site of King Wen of Zhou.
-
D.
Mount Shiun
Mount Shiun is a scenic mountain in Takamatsu, Japan, known as the forested backdrop to Ritsurin Garden and a popular spot for panoramic views over the city and Seto Inland Sea.
-
E.
Mount Jinba
Mount Jinba is a scenic mountain on the border of Tokyo and Kanagawa in Japan, popular for its hiking trails and panoramic views of the surrounding region, including Mount Fuji on clear days.
- F. None of above. chosen
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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f33509d08190b33775abb84d5255 |
completed | April 28, 2026, 5:49 p.m. |
Created at: April 16, 2026, 6:57 p.m.