Triple
T36095834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winterdown Comprehensive |
E1044055
|
entity |
| Predicate | hasFictionalCountrySetting |
P20932
|
FINISHED |
| Object | England |
—
|
NE NERFINISHED |
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: England | Statement: [Winterdown Comprehensive, hasFictionalCountrySetting, England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalCountrySetting Context triple: [Winterdown Comprehensive, hasFictionalCountrySetting, England]
-
A.
hasFictionalLocation
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
-
B.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
C.
locatedInFictionalCountry
chosen
Indicates that an entity exists or is situated within a country that is fictional rather than real.
-
D.
fictionalCountryMentioned
Indicates that a fictional or imaginary country is referenced or discussed in relation to an entity.
-
E.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
- 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_69f76e32d60c8190ba781ffaaab4aa3d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fff9b126b4819085a4cf8791d388d1 |
completed | May 10, 2026, 3:21 a.m. |
| PD | Predicate disambiguation | batch_69fff8f913a881908d3b7e490d92631f |
completed | May 10, 2026, 3:18 a.m. |
Created at: May 3, 2026, 4:08 p.m.