Triple
T1839947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babette |
E41151
|
entity |
| Predicate | hasDiminutiveType |
P456
|
FINISHED |
| Object | -ette suffix diminutive in French |
—
|
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: -ette suffix diminutive in French | Statement: [Babette, hasDiminutiveType, -ette suffix diminutive in French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiminutiveType Context triple: [Babette, hasDiminutiveType, -ette suffix diminutive in French]
-
A.
hasDiminutive
chosen
Indicates that one entity is a diminutive form or smaller/affectionate variant of another entity.
-
B.
hasAppellationType
Indicates that an entity’s name or title is associated with a specific category or type of appellation.
-
C.
hasThreeLetterForm
Indicates that an entity’s written or symbolic form consists of exactly three letters.
-
D.
hasLowercaseForm
Indicates that one entity is the lowercase version or representation of another entity.
-
E.
hasDemonym
Indicates that one entity is the term (demonym) used to refer to the inhabitants or natives of another entity (typically a place).
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafd88ebc81908208394746351fe6 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.