Triple
T21138175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echoing Sand Mountain |
E520865
|
entity |
| Predicate | hasChineseName |
P4878
|
FINISHED |
| Object | 鸣沙山 |
—
|
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: 鸣沙山 | Statement: [Echoing Sand Mountain, hasChineseName, 鸣沙山]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 鸣沙山 Context triple: [Echoing Sand Mountain, hasChineseName, 鸣沙山]
-
A.
Shapotou desert scenic area
Shapotou desert scenic area is a popular tourist destination in China’s Ningxia region, famed for its vast desert landscapes, Yellow River views, and adventure activities such as sand sledding and camel riding.
-
B.
Mingsha Sand Dunes
chosen
Mingsha Sand Dunes is a famous desert scenic area near Dunhuang in China, known for its towering sand hills, echoing sands, and views over the nearby Crescent Lake oasis.
-
C.
酒泉市
酒泉市 is a prefecture-level city in northwestern Gansu Province, China, known for its role in the ancient Silk Road and for hosting the Jiuquan Satellite Launch Center.
-
D.
长城
长城是中国古代为防御外敌入侵而修筑、绵延数千公里的巨大军事防御工程，也是世界著名的文化遗产与象征性建筑。
-
E.
嘉峪关市
嘉峪关市是位于中国甘肃省西北部、以明长城西端嘉峪关关城闻名的地级市和重要工业城市。
- 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7235d1c788190a28577a753532b2a |
completed | April 21, 2026, 7:12 a.m. |
Created at: April 16, 2026, 2:57 p.m.