Triple
T31849919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chang’an District, Xi’an |
E813036
|
entity |
| Predicate | hasSuburbanZone |
P198192
|
FINISHED |
| Object | rapidly expanding housing developments |
—
|
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: rapidly expanding housing developments | Statement: [Chang’an District, Xi’an, hasSuburbanZone, rapidly expanding housing developments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuburbanZone Context triple: [Chang’an District, Xi’an, hasSuburbanZone, rapidly expanding housing developments]
-
A.
isInSuburbanArea
Indicates that something is located within a suburban area, typically between urban and rural regions.
-
B.
isSuburbanArea
Indicates that a location is characterized as a suburban area, typically lying between urban and rural regions and exhibiting suburban development patterns.
-
C.
hasSuburbanSection
Indicates that a larger route, line, or area includes a portion that passes through or serves a suburban region.
-
D.
isSuburbanDistrict
Indicates that a district is located in and characterized as part of the suburbs of a larger urban area.
-
E.
isSuburbanResidentialArea
Indicates that a location is primarily a residential neighborhood situated in a suburban (non-urban, non-rural) setting.
- F. None of above. chosen
Provenance (4 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_69f348eb327881909b4584b925742f6e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fed09a12648190affcd9bacf7ca275 |
completed | May 9, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69fecf91d6f481908deb60c965c433ed |
completed | May 9, 2026, 6:09 a.m. |
| PDg | Predicate description generation | batch_69fed098328c819085979de6b179b378 |
completed | May 9, 2026, 6:13 a.m. |
Created at: April 30, 2026, 11:51 p.m.