Triple
T9146043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lu Xun Museum (Shanghai) |
E219456
|
entity |
| Predicate | hasArchitecturalFunction |
P22013
|
FINISHED |
| Object | exhibition space |
—
|
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: exhibition space | Statement: [Lu Xun Museum (Shanghai), hasArchitecturalFunction, exhibition space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArchitecturalFunction Context triple: [Lu Xun Museum (Shanghai), hasArchitecturalFunction, exhibition space]
-
A.
hasArchitecturalFeature
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
-
B.
architecturalUse
chosen
Indicates how a structure, space, or element is intended to be used or function within an architectural context.
-
C.
hasArchitecturalSignificance
Indicates that something possesses notable architectural qualities, importance, or influence that make it worthy of special attention or recognition.
-
D.
architecturalConcept
Indicates that one entity represents or embodies an architectural concept in relation to another entity.
-
E.
architecturalWork
Indicates that one entity is an architectural creation (such as a building or structure) designed or realized by another entity.
- 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_69ca83e121dc81909912bd66953081c5 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca917914c8190b97ca9169bbd1e5e |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6603ce8c8190bf6e8d6754bdec54 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:19 p.m.