Triple
T32383647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taiyuan dialect |
E827488
|
entity |
| Predicate | usesStandardWriting |
P128905
|
FINISHED |
| Object | Written Mandarin Chinese |
—
|
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: Written Mandarin Chinese | Statement: [Taiyuan dialect, usesStandardWriting, Written Mandarin Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesStandardWriting Context triple: [Taiyuan dialect, usesStandardWriting, Written Mandarin Chinese]
-
A.
usesWriting
chosen
Indicates that one entity employs or applies a particular writing system, script, or written form for communication or representation.
-
B.
usesStandard
Indicates that one entity adopts, follows, or operates according to a specified standard defined by another entity or reference.
-
C.
wasStandardTextUntil
Indicates that something functioned or was treated as the standard or default text up until a specified point in time.
-
D.
canBeWrittenIn
Indicates that something is capable of being expressed, encoded, or represented using a particular language, notation, or medium.
-
E.
usesWritingsOf
Indicates that one entity makes use of, relies on, or draws from the writings or written works produced by another entity.
- 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_69f349177ddc8190ab0583f05597056b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
Created at: May 1, 2026, 12:51 a.m.