Triple
T21132765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Épisode de la vie d’un artiste |
E520729
|
entity |
| Predicate | yearOfFirstUseAsProgram |
P24583
|
FINISHED |
| Object | 1830 |
—
|
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: 1830 | Statement: [Épisode de la vie d’un artiste, yearOfFirstUseAsProgram, 1830]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfFirstUseAsProgram Context triple: [Épisode de la vie d’un artiste, yearOfFirstUseAsProgram, 1830]
-
A.
firstYearOfUse
chosen
Indicates the year in which something was first put into use or began being used.
-
B.
beganInYear
Indicates that an event, process, or state started in a specific calendar year.
-
C.
firstUsedOn
Indicates the date, time, or context in which something was initially applied, activated, or put into use on a particular object or entity.
-
D.
yearOfUse
Indicates the specific year during which something was in use or actively utilized.
-
E.
developedSince
Indicates that something has been created, expanded, or advanced starting from a specified point in time and continuing thereafter.
- 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e723574b1481909fe9bebc83f1f3ce |
completed | April 21, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e5f5ed6c8c8190b31092a5d4c3de5d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:56 p.m.