Triple
T64833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vietnamese alphabet |
E1288
|
entity |
| Predicate | replacedWritingSystem |
P4435
|
FINISHED |
| Object | chữ Nôm |
—
|
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: chữ Nôm | Statement: [Vietnamese alphabet, replacedWritingSystem, chữ Nôm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replacedWritingSystem Context triple: [Vietnamese alphabet, replacedWritingSystem, chữ Nôm]
-
A.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
B.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
-
C.
replacedCurrency
Indicates that one currency has been superseded and no longer used because another currency has taken its place.
-
D.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
-
E.
hasWritingDirection
Indicates the direction in which writing or text is read or written for a given script, language, or text system.
- F. None of above. chosen
Provenance (4 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2516eda54819090f5c14384d4eab1 |
completed | Feb. 28, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69a24ea5c140819080409a968c8d2ce8 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a2516d98e88190b79261bd3fcadd9b |
completed | Feb. 28, 2026, 2:22 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.