Triple
T34940308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 王屋山 |
E1007696
|
entity |
| Predicate | 主要景观特色 |
P84159
|
FINISHED |
| Object | 山岳景观 |
—
|
LITERAL 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: 山岳景观 | Statement: [王屋山, 主要景观特色, 山岳景观]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 主要景观特色 Context triple: [王屋山, 主要景观特色, 山岳景观]
-
A.
立地特性
Indicates the characteristics or qualities of a location that define its situational conditions or advantages in relation to its surroundings.
-
B.
生态定位
Indicates the ecological role or niche an organism occupies within its environment, including its functional position and interactions in the ecosystem.
-
C.
scenicCategory
Indicates the classification of a place or route based on its visual appeal or scenic qualities.
-
D.
校园环境特点
Indicates the characteristic features or qualities that define the environment of a campus.
-
E.
tourismCharacteristic
chosen
Indicates that something has a specific feature, quality, or attribute relevant to tourism, such as what makes a place, service, or activity notable or suitable for tourists.
- F. None of above.
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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.