Triple
T127839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bentley Priory |
E2587
|
entity |
| Predicate | hasVisitorAttraction |
P530
|
FINISHED |
| Object | Bentley Priory Museum tours |
—
|
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: Bentley Priory Museum tours | Statement: [Bentley Priory, hasVisitorAttraction, Bentley Priory Museum tours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisitorAttraction Context triple: [Bentley Priory, hasVisitorAttraction, Bentley Priory Museum tours]
-
A.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
B.
hasThemePark
Indicates that one entity owns, contains, or is associated with a theme park as part of its properties or offerings.
-
C.
isTouristDestination
chosen
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
-
D.
hasWaterPark
Indicates that one entity possesses, includes, or features a water park as part of its facilities or attributes.
-
E.
hasHistoricSite
Indicates that an entity possesses, contains, or is associated with a place recognized for its historical significance.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25763ccf8819094e8dffb2ff98480 |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564c11208190ad25495609d94d87 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.