Triple
T28262475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’amour est un oiseau rebelle |
E712616
|
entity |
| Predicate | operaSettingPeriod |
P128598
|
FINISHED |
| Object | early 19th century |
—
|
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: early 19th century | Statement: [L’amour est un oiseau rebelle, operaSettingPeriod, early 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operaSettingPeriod Context triple: [L’amour est un oiseau rebelle, operaSettingPeriod, early 19th century]
-
A.
mainSettingPeriod
Indicates the historical or temporal period in which the primary setting of a work or event takes place.
-
B.
settingPeriodDuration
Indicates the length of time for which a particular setting or configuration remains in effect.
-
C.
settingDepictedPeriod
Indicates the historical or temporal period in which the setting of something (e.g., a work or scene) is depicted.
-
D.
fromOperaSetIn
Indicates that an opera originates from or is part of a narrative that is set in a particular place or setting.
-
E.
eraOfSetting
chosen
Indicates the historical or temporal period in which the setting of something (such as a story, event, or work) takes 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fe831c97c88190b27ecf100e25c2a0 |
completed | May 9, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69fe7f1b92648190b14e56bcaee5d0ca |
completed | May 9, 2026, 12:26 a.m. |
Created at: April 27, 2026, 11:12 p.m.