Triple
T15639453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuhan suburban districts |
E376028
|
entity |
| Predicate | includeAreaType |
P36978
|
FINISHED |
| Object | suburban residential communities |
—
|
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: suburban residential communities | Statement: [Wuhan suburban districts, includeAreaType, suburban residential communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includeAreaType Context triple: [Wuhan suburban districts, includeAreaType, suburban residential communities]
-
A.
includesAreaType
chosen
Indicates that one entity encompasses or contains another entity of a specified area type within its scope or boundaries.
-
B.
includesAreaOf
Indicates that one entity encompasses or contains the spatial extent or area covered by another entity.
-
C.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
typeOfAreaRepresented
Indicates that one entity specifies the kind or category of area that another entity represents.
-
E.
areaServedType
Indicates the type or category of area that is served by an entity or service.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed06b388190bfebb77fe70e7df1 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.