Triple
T6246776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qinling Mountains |
E139738
|
entity |
| Predicate | ChineseName |
P744
|
FINISHED |
| Object | 秦岭 |
E139738
|
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: 秦岭 | Statement: [Qinling Mountains, ChineseName, 秦岭]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 秦岭 Context triple: [Qinling Mountains, ChineseName, 秦岭]
-
A.
Qinling Mountains
chosen
The Qinling Mountains are a major east–west mountain range in central China that form a natural climatic and geographical boundary between northern and southern China.
-
B.
Taihang Mountains
The Taihang Mountains are a major mountain range in northern China, forming a natural boundary between the Loess Plateau and the North China Plain and known for their steep cliffs and scenic gorges.
-
C.
长白山
长白山是一座位于中朝边界、以火山天池和丰富自然资源闻名的著名高山与风景名胜区。
-
D.
Mount Hua
Mount Hua is one of China’s Five Great Mountains, renowned for its steep granite peaks, ancient Taoist temples, and dramatic cliffside trails in central China.
-
E.
Qionglai Mountains
The Qionglai Mountains are a major mountain range in Sichuan, China, known for their high peaks, deep valleys, and role as a key part of the eastern edge of the Tibetan Plateau.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0631f511c81908d413320efdce42e |
completed | March 22, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c2440e47108190b07fa65db104e773 |
completed | March 24, 2026, 7:58 a.m. |
Created at: March 22, 2026, 4:23 p.m.