Triple
T4019441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhan |
E91243
|
entity |
| Predicate | romanizationStandard |
P23170
|
FINISHED |
| Object | Mainland China standard Mandarin |
—
|
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: Mainland China standard Mandarin | Statement: [Zhan, romanizationStandard, Mainland China standard Mandarin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanizationStandard Context triple: [Zhan, romanizationStandard, Mainland China standard Mandarin]
-
A.
hasRomanizationStandard
chosen
Indicates that an entity’s romanized form follows a specified romanization standard or system.
-
B.
standardTransliteration
Indicates that one representation of text is a transliteration of another according to a recognized standard or convention.
-
C.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
-
D.
partlyRomanized
Indicates that an entity has been converted into the Roman (Latin) script only in part, with some portions remaining in another script or unchanged.
-
E.
writingSystemStandardized
Indicates that a writing system has been formally codified and regulated according to an accepted standard or set of rules.
- 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_69aed9618b04819081750d979d2af098 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaab39d4819080e37cd175c89542 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8fc78ec819092d4dab88d85a141 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:35 p.m.