Triple
T22402940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhanqiao Pier |
E553804
|
entity |
| Predicate | imageMotifOf |
P41002
|
FINISHED |
| Object | Qingdao tourism promotions |
—
|
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: Qingdao tourism promotions | Statement: [Zhanqiao Pier, imageMotifOf, Qingdao tourism promotions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageMotifOf Context triple: [Zhanqiao Pier, imageMotifOf, Qingdao tourism promotions]
-
A.
transformationMotif
Indicates a recurring pattern or theme in which one entity undergoes a change in form, state, or identity in relation to another.
-
B.
featuresMotif
chosen
Indicates that something contains, incorporates, or prominently includes a particular recurring motif or pattern.
-
C.
imageOf
Indicates that one entity is a visual representation or depiction of another entity.
-
D.
evokesImageOf
Indicates that one entity triggers or brings to mind a mental image or visual representation of another entity.
-
E.
usesMotifsFrom
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b565c48190b0f6c19f17995b40 |
completed | April 29, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
Created at: April 16, 2026, 8:46 p.m.