Triple
T38599458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiordiligi |
E934168
|
entity |
| Predicate | timePeriodOfOperaSetting |
P123135
|
FINISHED |
| Object | 18th 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: 18th century | Statement: [Fiordiligi, timePeriodOfOperaSetting, 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfOperaSetting Context triple: [Fiordiligi, timePeriodOfOperaSetting, 18th century]
-
A.
mainSettingPeriod
chosen
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.
timePeriod
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
D.
sessionLength
Indicates the duration of time that a particular session lasts from start to end.
-
E.
timeSettingVariant
Indicates a relationship where one time setting is an alternative or modified version of another time setting.
- 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_69f76ecc17688190b389b693a5927501 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd8e5f7c4c8190ab8e2f2a7bb1bd79 |
completed | May 8, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fd8d8a16f08190b9e880901bfa44fe |
completed | May 8, 2026, 7:15 a.m. |
Created at: May 3, 2026, 4:32 p.m.