Triple
T3015338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu Chinese |
E82322
|
entity |
| Predicate | hasRepresentativeDialect |
P4251
|
FINISHED |
| Object | Shanghai dialect |
—
|
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: Shanghai dialect | Statement: [Wu Chinese, hasRepresentativeDialect, Shanghai dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRepresentativeDialect Context triple: [Wu Chinese, hasRepresentativeDialect, Shanghai dialect]
-
A.
hasDialects
chosen
Indicates that an entity (typically a language) possesses one or more distinct dialectal varieties.
-
B.
hasMajorDialectGroup
Indicates that an entity (typically a language) is associated with a primary or major dialect group to which it belongs.
-
C.
hasLanguageRepresentation
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
-
D.
hasTraditionalDialect
Indicates that an entity possesses or is associated with a traditional form or variety of a language or dialect.
-
E.
hasDialectContinuumWith
Indicates that two languages or dialects are part of a continuous chain of mutually intelligible varieties, without a clear boundary separating them.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a6b37288190a6965d183ca4b08b |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad961a97188190809dc73430a8eda8 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.