Triple
T21938396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Portuguese |
E541752
|
entity |
| Predicate | hasWritingConvention |
P67410
|
FINISHED |
| Object | use of diacritics such as acute, circumflex and tilde |
—
|
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: use of diacritics such as acute, circumflex and tilde | Statement: [European Portuguese, hasWritingConvention, use of diacritics such as acute, circumflex and tilde]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWritingConvention Context triple: [European Portuguese, hasWritingConvention, use of diacritics such as acute, circumflex and tilde]
-
A.
hasOrthographicConvention
chosen
Indicates that there is a specific writing or spelling convention that governs how something is represented in written form.
-
B.
isWrittenWith
Indicates that something is created or expressed using a particular writing tool, medium, or system.
-
C.
hasWrittenForm
Indicates that an entity is associated with a specific written or textual representation.
-
D.
mannerOfWriting
Indicates the way or style in which something is written or expressed in writing.
-
E.
canBeWrittenIn
Indicates that something is capable of being expressed, encoded, or represented using a particular language, notation, or medium.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1241e35bc81909eb3225d5cd97b92 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:55 p.m.