Triple
T17301445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan |
E420047
|
entity |
| Predicate | setInFictionalSettingType |
P18263
|
FINISHED |
| Object | near-future society |
—
|
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: near-future society | Statement: [Susan, setInFictionalSettingType, near-future society]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setInFictionalSettingType Context triple: [Susan, setInFictionalSettingType, near-future society]
-
A.
setInFictionalLocation
chosen
Indicates that an event, story, or narrative takes place within a fictional or imagined location rather than a real-world setting.
-
B.
setInFictionalOrRealLocation
Indicates that something (such as a story, event, or scene) takes place within a specified location, whether that location is real or fictional.
-
C.
setInFictionalizedRegionOf
Indicates that an event or narrative is located within a region that is a fictionalized or altered version of a real-world place.
-
D.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
-
E.
laterSettingOfFiction
Indicates that one fictional work is set chronologically later than another within a shared narrative or story world.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e438fae8848190a06c5866e606baac |
completed | April 19, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69e3b0118ad08190b119cd219c68ba67 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:41 a.m.