Triple
T18166589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lufton |
E434910
|
entity |
| Predicate | hasFictionalLocationAssociation |
P84403
|
FINISHED |
| Object | English countryside |
—
|
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: English countryside | Statement: [Lufton, hasFictionalLocationAssociation, English countryside]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalLocationAssociation Context triple: [Lufton, hasFictionalLocationAssociation, English countryside]
-
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.
fictionalLocationAssociatedWith
chosen
Indicates a relationship where a fictional entity (such as a character, event, or work) is connected to or set in a particular fictional location.
-
C.
hasBranchInFictionalLocation
Indicates that an organization maintains a branch, office, or presence within a fictional or imaginary location.
-
D.
hasFictionalLandmark
Indicates that one entity includes, features, or is associated with a landmark that is fictional rather than real.
-
E.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec7e41c8190bd19dc5f62c69608 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.