Triple
T33700132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aimwell |
E863431
|
entity |
| Predicate | periodOfFictionalSetting |
P180185
|
FINISHED |
| Object | early 18th century England |
—
|
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 18th century England | Statement: [Aimwell, periodOfFictionalSetting, early 18th century England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: periodOfFictionalSetting Context triple: [Aimwell, periodOfFictionalSetting, early 18th century England]
-
A.
workOfFictionSetting
Indicates that a work of fiction is set in, or primarily takes place within, a particular location, time, or environment.
-
B.
associatedWithFictionalSetting
Indicates that an entity has a connection or relevance to a particular fictional setting or universe.
-
C.
basedInFictionalSetting
Indicates that an entity’s primary location or setting exists within a fictional or imaginary world rather than the real world.
-
D.
fictionalSettingRegion
Indicates that a fictional setting is located within or associated with a specific geographic or administrative region.
-
E.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
- F. None of above. chosen
Provenance (4 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
| PDg | Predicate description generation | batch_69f73221eef88190bd8905e6e9f5a586 |
completed | May 3, 2026, 11:31 a.m. |
Created at: May 1, 2026, 1:43 a.m.