Triple
T34940327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 王屋山 |
E1007696
|
entity |
| Predicate | 相关文化主题 |
P78619
|
FINISHED |
| Object | 愚公精神 |
—
|
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: 愚公精神 | Statement: [王屋山, 相关文化主题, 愚公精神]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 相关文化主题 Context triple: [王屋山, 相关文化主题, 愚公精神]
-
A.
culturalThemes
chosen
Indicates that there is a relationship between entities where one embodies, expresses, or is associated with particular cultural themes present in or derived from the other.
-
B.
cultureRelatedTo
Indicates a relationship where one entity is connected, associated, or relevant to the culture, traditions, or cultural context of another entity.
-
C.
culturalType
Indicates the classification of something according to its cultural category, style, or tradition.
-
D.
culturalCategory
Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
-
E.
culturalIssueExploredIn
Indicates that a particular cultural issue is examined, addressed, or thematically treated within a specified work or context.
- 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.