Triple
T64787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vietnamese alphabet |
E1288
|
entity |
| Predicate | hasToneMarks |
P2270
|
FINISHED |
| Object | five tone marks |
—
|
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: five tone marks | Statement: [Vietnamese alphabet, hasToneMarks, five tone marks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToneMarks Context triple: [Vietnamese alphabet, hasToneMarks, five tone marks]
-
A.
usesDiacritics
chosen
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
B.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
-
C.
hasBasicLetters
Indicates that an entity contains or is composed of fundamental alphabetic characters, without additional symbols or diacritics.
-
D.
hasOfficialOrthography
Indicates that an entity has a formally recognized and standardized system for writing its language or name.
-
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.
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_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. |
Created at: Feb. 28, 2026, 2:02 a.m.