Triple
T10676570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grégoire |
E251632
|
entity |
| Predicate | accentType |
P18659
|
FINISHED |
| Object | acute accent on e |
—
|
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: acute accent on e | Statement: [Grégoire, accentType, acute accent on e]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accentType Context triple: [Grégoire, accentType, acute accent on e]
-
A.
hasAccent
Indicates that an entity speaks with or possesses a particular accent or distinctive pronunciation style.
-
B.
accentedFormOf
Indicates that one linguistic form is an accented or diacritically marked variant of another, more basic form.
-
C.
notationType
Indicates the specific system or style of notation used to represent or encode something (such as music, math, or language).
-
D.
characterStyle
Indicates how a character is visually or typographically presented, such as its font, weight, size, or decorative attributes.
-
E.
diacriticType
chosen
Indicates the specific kind or category of diacritic mark associated with a character or symbol.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fb94b05c8190b66bf64f5c6d166b |
completed | April 9, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8a93208190a573061387e2aebb |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:09 p.m.