Triple
T32383561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanchang dialect |
E827484
|
entity |
| Predicate | isUrbanKoinéFor |
P174010
|
FINISHED |
| Object | Gan speakers in Nanchang |
—
|
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: Gan speakers in Nanchang | Statement: [Nanchang dialect, isUrbanKoinéFor, Gan speakers in Nanchang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanKoinéFor Context triple: [Nanchang dialect, isUrbanKoinéFor, Gan speakers in Nanchang]
-
A.
isUrbanForm
Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
-
B.
isUrbanService
Indicates that a service operates within or is specifically intended for an urban area or city environment.
-
C.
isUrbanHubFor
Indicates that a location functions as a central urban focal point or primary service center for another area or population.
-
D.
isUrbanAxis
Indicates that something functions as a primary structural or organizational line within an urban area, such as a main street, corridor, or development spine that shapes the city’s form or activity.
-
E.
isUrbanSee
Indicates a relationship where a location or area is recognized or classified as an urban settlement or city-like environment.
- 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_69f349177ddc8190ab0583f05597056b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1cde63c8190ad546f0a9b61b2a1 |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
| PDg | Predicate description generation | batch_69f6bb344bb48190a8089f29c0063ded |
completed | May 3, 2026, 3:04 a.m. |
Created at: May 1, 2026, 12:51 a.m.