Triple
T14787202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 太庙 |
E347557
|
entity |
| Predicate | 所属文化 |
P1439
|
FINISHED |
| Object | 中华传统礼制文化 |
—
|
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: 中华传统礼制文化 | Statement: [太庙, 所属文化, 中华传统礼制文化]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 所属文化 Context triple: [太庙, 所属文化, 中华传统礼制文化]
-
A.
culturalType
Indicates the classification of something according to its cultural category, style, or tradition.
-
B.
culturalCategory
Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
-
C.
hasAssociatedCulture
chosen
Indicates that an entity is related to, influenced by, or characterized by a particular culture.
-
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.
hasCulturalScope
Indicates that a relationship or action is limited to, relevant within, or characterized by a particular cultural context or domain.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decaa083e481908336d58d026eec32 |
completed | April 14, 2026, 11:15 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.