Triple
T64837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vietnamese alphabet |
E1288
|
entity |
| Predicate | hasCaseDistinction |
P2204
|
FINISHED |
| Object | uppercase and lowercase |
—
|
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: uppercase and lowercase | Statement: [Vietnamese alphabet, hasCaseDistinction, uppercase and lowercase]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCaseDistinction Context triple: [Vietnamese alphabet, hasCaseDistinction, uppercase and lowercase]
-
A.
hasCaseInflection
Indicates that a word or phrase changes form to reflect grammatical case (such as nominative, accusative, etc.) in a given language context.
-
B.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
C.
letterCase
chosen
Indicates the relationship between a character or string and its typographical case (such as uppercase, lowercase, or mixed case).
-
D.
isDistinctFrom
Indicates that two entities are not identical and can be clearly distinguished from one another.
-
E.
hasUppercaseAndLowercase
Indicates that a string or text value contains at least one uppercase letter and at least one lowercase letter.
- 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.