Triple
T13014837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quanshan District |
E322522
|
entity |
| Predicate | isBuiltUpAreaOf |
P105265
|
FINISHED |
| Object | Xuzhou urban core |
—
|
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: Xuzhou urban core | Statement: [Quanshan District, isBuiltUpAreaOf, Xuzhou urban core]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBuiltUpAreaOf Context triple: [Quanshan District, isBuiltUpAreaOf, Xuzhou urban core]
-
A.
isIndustrialAreaOf
Indicates that a location functions primarily as an industrial zone or district associated with a specified area or jurisdiction.
-
B.
isBuildingOf
Indicates that one entity is a building that belongs to, houses, or is associated with another entity (such as an organization, institution, or complex).
-
C.
isUrbanZoneFor
Indicates that a given area functions as an urban zone designated for a particular entity or purpose.
-
D.
isSuburbanResidentialArea
Indicates that a location is primarily a residential neighborhood situated in a suburban (non-urban, non-rural) setting.
-
E.
isUrbanAreaOfType
chosen
Indicates that a given area is classified as belonging to a specific type or category of urban area (e.g., city, town, suburb).
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecd04748190ade2530ee5db35fe |
completed | April 10, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69d97dc153a081909d13a694993f074a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:50 p.m.