Triple
T6533634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anglers’ Rest |
E152291
|
entity |
| Predicate | locatedInFictionalAreaType |
P21117
|
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: [Anglers’ Rest, locatedInFictionalAreaType, English countryside]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInFictionalAreaType Context triple: [Anglers’ Rest, locatedInFictionalAreaType, English countryside]
-
A.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
B.
locatedInFictionalCountry
Indicates that an entity exists or is situated within a country that is fictional rather than real.
-
C.
residesInFictionalLocation
Indicates that an entity lives or is based in a location that is explicitly fictional or imaginary.
-
D.
hasFictionalLocation
chosen
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.
-
E.
locatedNearFiction
Indicates that one fictional entity or place is situated close to another within an imagined or narrative context.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adbf3a748190b0fb52122faaf6d3 |
completed | March 27, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69c68abd9c7c819099e4fe8097cd1b28 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:46 p.m.