Triple
T262205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China |
E5561
|
entity |
| Predicate | standardScript |
P6524
|
FINISHED |
| Object | Simplified Chinese (mainland) |
—
|
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: Simplified Chinese (mainland) | Statement: [China, standardScript, Simplified Chinese (mainland)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardScript Context triple: [China, standardScript, Simplified Chinese (mainland)]
-
A.
primaryScript
chosen
Indicates the writing system or script that is chiefly used to represent the language or content of an entity.
-
B.
script
Indicates that an entity is associated with a written text or code (such as a screenplay, program, or written instructions) that defines its content or behavior.
-
C.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
D.
scriptType
Indicates the classification or category of a script, specifying what kind of script it is (e.g., its format, purpose, or scripting language type).
-
E.
scriptDirection
Indicates the direction in which a writing system or script is read or written (e.g., left-to-right, right-to-left, top-to-bottom).
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e2aba74819093eddd8d820260c0 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b6c968c819094fc903a3a377e15 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.