Triple
T10526016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera |
E248306
|
entity |
| Predicate | workFictionalTimeSetting |
P18945
|
FINISHED |
| Object | 1930s |
—
|
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: 1930s | Statement: [Vera, workFictionalTimeSetting, 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workFictionalTimeSetting Context triple: [Vera, workFictionalTimeSetting, 1930s]
-
A.
fictionalTime
Indicates that the associated time or temporal reference exists only within a fictional or imagined context, rather than in real-world chronology.
-
B.
laterSettingOfFiction
Indicates that one fictional work is set chronologically later than another within a shared narrative or story world.
-
C.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
D.
fictionalEra
chosen
Indicates the time period or age within a fictional or imaginary setting in which an entity exists or an event occurs.
-
E.
settingOfFictionalLife
Indicates that a particular place or environment serves as the primary backdrop or context in which a fictional character’s life and experiences occur.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f4bbe88190bce7789a56c85671 |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb94fa10819091f585bab4379c6f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:29 p.m.