Triple
T31949847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 城门楼 |
E815748
|
entity |
| Predicate | 相关建筑 |
P128371
|
FINISHED |
| Object | 城墙 |
—
|
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: 城墙 | Statement: [城门楼, 相关建筑, 城墙]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 相关建筑 Context triple: [城门楼, 相关建筑, 城墙]
-
A.
建築運動
Indicates a relationship where an entity is involved in or characterized by an architectural movement or campaign related to building design and construction.
-
B.
appliedToBuilding
Indicates that something (such as a process, treatment, regulation, or attribute) is directed toward, implemented on, or otherwise affects a building.
-
C.
architectureAssociated
Indicates that there is a relationship or connection between an entity and a particular architectural style, feature, or practice.
-
D.
buildings
chosen
Indicates that one or more buildings are associated with, located at, or relevant to the referenced entity.
-
E.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
- 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_69f348f42d188190a33fc8d20ec50517 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b2a905d081909cf5fbedd1181a1a |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:07 a.m.