Triple
T32920217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiang group of Chinese dialects |
E842123
|
entity |
| Predicate | representativeUrbanVariety |
P5973
|
FINISHED |
| Object | Changsha dialect |
—
|
NE NERFINISHED |
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: Changsha dialect | Statement: [Xiang group of Chinese dialects, representativeUrbanVariety, Changsha dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representativeUrbanVariety Context triple: [Xiang group of Chinese dialects, representativeUrbanVariety, Changsha dialect]
-
A.
isMajorUrbanVarietyOf
Indicates that one linguistic variety is the primary urban form or dialect of another, more general language or variety.
-
B.
representsUrbanArea
Indicates that the referenced entity corresponds to, or is classified as, an urban area (such as a city or town) within a given context.
-
C.
varietyOf
Indicates that one entity is a specific type, kind, or variant of another, more general entity.
-
D.
typicalVariety
chosen
Indicates that one entity is a representative or characteristic example of the variety or type defined by another entity.
-
E.
representsCity
Indicates that one entity serves as the official representative or embodiment of a particular city.
- 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_69f3494779388190a5d3e97f92278be2 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fecd0a732c819097bdd3eb69b6158c |
completed | May 9, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69fecc0318d481908b5b20598a76a9fe |
completed | May 9, 2026, 5:54 a.m. |
Created at: May 1, 2026, 1:19 a.m.