Triple
T35765022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiegong Temple |
E1033990
|
entity |
| Predicate | partOfCityscape |
P119773
|
FINISHED |
| Object | Jinan historical and cultural landscape |
—
|
NE NERFINISHED |
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: Jinan historical and cultural landscape | Statement: [Tiegong Temple, partOfCityscape, Jinan historical and cultural landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfCityscape Context triple: [Tiegong Temple, partOfCityscape, Jinan historical and cultural landscape]
-
A.
partOfSkylineOf
Indicates that one entity is a visible component or feature contributing to the overall skyline profile of another entity, typically a city or urban area.
-
B.
isPartOfStreetscape
Indicates that something forms a component or element within the overall layout or visual composition of a streetscape.
-
C.
partOfUrbanLayout
chosen
Indicates that one entity is a component or constituent element within the overall structure or organization of an urban area.
-
D.
urbanLandscapeCharacterizedBy
Indicates that an urban landscape possesses or is defined by specific distinguishing features, qualities, or elements.
-
E.
cityScene
Indicates a scene or setting that takes place within an urban or city environment.
- 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_69f76e13edd081909101629aa829c4ad |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00a74c0564819081e1c4c29b9d0d15 |
completed | May 10, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_6a00a6a63ef48190a743c88534d9d672 |
completed | May 10, 2026, 3:39 p.m. |
Created at: May 3, 2026, 4:06 p.m.