Triple
T14787218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 太庙 |
E347557
|
entity |
| Predicate | 宗教属性 |
P33575
|
FINISHED |
| Object | 祭祀祖先的礼制建筑 |
—
|
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: 祭祀祖先的礼制建筑 | Statement: [太庙, 宗教属性, 祭祀祖先的礼制建筑]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 宗教属性 Context triple: [太庙, 宗教属性, 祭祀祖先的礼制建筑]
-
A.
religiousCharacteristic
chosen
Indicates that one entity has a religious attribute, quality, or affiliation that characterizes or distinguishes it in a religious context.
-
B.
religiousAffiliation
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
C.
religiousFoundation
Indicates that an entity was established, created, or founded by a religious organization, authority, or tradition.
-
D.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
E.
religiousSceneSpecialization
Indicates a relationship where a scene is specifically characterized or classified by a particular religious theme, context, or function.
- 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.