Triple
T36263767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VisitEngland Quality Assured Visitor Attraction |
E892165
|
entity |
| Predicate | hasQualityDimension |
P50251
|
FINISHED |
| Object | service quality |
—
|
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: service quality | Statement: [VisitEngland Quality Assured Visitor Attraction, hasQualityDimension, service quality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQualityDimension Context triple: [VisitEngland Quality Assured Visitor Attraction, hasQualityDimension, service quality]
-
A.
hasQualityCriterion
chosen
Indicates that something is associated with a specific standard or criterion used to judge its quality.
-
B.
hasQualityModel
Indicates that an entity is associated with or characterized by a specific quality model.
-
C.
hasIndividualDimension
Indicates that an entity possesses a specific, separately identifiable dimension or measurable extent as an individual attribute.
-
D.
hasDimensionality
Indicates that an entity possesses a specific number of dimensions or a particular dimensional structure.
-
E.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
- 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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.