Triple
T22274249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelly et Monsieur Arnaud |
E550558
|
entity |
| Predicate | ageDifferenceBetweenLeadsDepicted |
P125146
|
FINISHED |
| Object | significant |
—
|
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: significant | Statement: [Nelly et Monsieur Arnaud, ageDifferenceBetweenLeadsDepicted, significant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageDifferenceBetweenLeadsDepicted Context triple: [Nelly et Monsieur Arnaud, ageDifferenceBetweenLeadsDepicted, significant]
-
A.
numberOfAges
Indicates the count of distinct ages associated with an entity or within a specified group or context.
-
B.
depictsAgeContrast
Indicates a relationship where one entity visually represents or highlights a contrast in age between two or more entities.
-
C.
relativeAgeStatus
chosen
Indicates a comparative relationship specifying how the age of one entity relates to the age of another (e.g., older, younger, or same age).
-
D.
ageVariants
Indicates that one entity is an alternative form or version of another distinguished specifically by age (e.g., younger/older or different life-stage variants).
-
E.
ageDepictionConsistency
Indicates that the depicted age of an entity is consistent with its known or expected age within the given context.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f14ea643d48190985371d01aac7bfc |
completed | April 29, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e72ff0363081909f794d19c8a64837 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:40 p.m.