Triple
T18442470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenzhen metropolitan area |
E450564
|
entity |
| Predicate | belongsToUrbanSystem |
P38993
|
FINISHED |
| Object | Chinese coastal urban belt |
—
|
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: Chinese coastal urban belt | Statement: [Shenzhen metropolitan area, belongsToUrbanSystem, Chinese coastal urban belt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToUrbanSystem Context triple: [Shenzhen metropolitan area, belongsToUrbanSystem, Chinese coastal urban belt]
-
A.
belongsToUrbanZone
Indicates that something is located within, or is a part of, a designated urban zone or area.
-
B.
hasUrbanRelation
Indicates a relationship where one entity is connected to another through an urban context, such as city-based location, influence, or interaction.
-
C.
belongsToUrbanCorridor
chosen
Indicates that something is part of, contained within, or functionally integrated into a continuous urban corridor or urbanized area.
-
D.
formsUrbanAreaWith
Indicates that two or more settlements are geographically and functionally connected so that together they constitute a single continuous urban area.
-
E.
hasUrbanLocalities
Indicates that an entity possesses or includes one or more urban localities within its jurisdiction or scope.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c11b1288190b9ed4497751197d1 |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.