Triple
T8903767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 蛇山 |
E211994
|
entity |
| Predicate | 文化属性 |
P81632
|
FINISHED |
| Object | 历史文化景观 |
—
|
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: 历史文化景观 | Statement: [蛇山, 文化属性, 历史文化景观]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 文化属性 Context triple: [蛇山, 文化属性, 历史文化景观]
-
A.
culturalType
chosen
Indicates the classification of something according to its cultural category, style, or tradition.
-
B.
cultureCharacteristic
Indicates that a particular trait, practice, or feature is a defining characteristic of a given culture.
-
C.
culturalCategory
Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
-
D.
culturalLayer
Indicates the relationship in which something belongs to, originates from, or is associated with a particular cultural stratum, tradition, or level within a culture.
-
E.
culturalKnowledge
Indicates that one entity possesses or conveys understanding of the customs, practices, values, or traditions associated with a particular culture.
- 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc64c2509881908fb692522d348e96 |
completed | April 1, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69cc5ecf55248190a29f00fbf99f13c4 |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:55 p.m.