Triple
T10634307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamagata Prefecture |
E250538
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Zao Mountains |
E586512
|
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: Zao Mountains | Statement: [Yamagata Prefecture, contains, Zao Mountains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zao Mountains Context triple: [Yamagata Prefecture, contains, Zao Mountains]
-
A.
Zao Mountains
chosen
Zao Mountains is a volcanic mountain range in northeastern Japan known for its ski resorts, hot springs, and the crater lake Okama.
-
B.
Wuzhi Mountain
Wuzhi Mountain is a prominent, five-peaked mountain in Hainan, China, renowned as the island’s highest point and a symbol of its natural landscape.
-
C.
Wuling Mountain
Wuling Mountain is a prominent peak in northern China known as the highest summit of the Yan Mountains range.
-
D.
Lao Mountain
Lao Mountain is a prominent coastal mountain range in eastern China known for its granite peaks, Taoist temples, and scenic views over the Yellow Sea.
-
E.
Xuedou Mountain
Xuedou Mountain is a scenic and historically significant mountain area in Zhejiang Province, China, known for its Buddhist temples, waterfalls, and natural beauty.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfab47bc819086684edc1b6dce74 |
completed | April 8, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96bbd64d8819089d55af875d39e45 |
completed | April 10, 2026, 9:29 p.m. |
Created at: April 8, 2026, 9:03 p.m.