Triple
T28873771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackpool Illuminations |
E732206
|
entity |
| Predicate | primaryTransportExperience |
P22360
|
FINISHED |
| Object | driving or riding along the seafront |
—
|
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: driving or riding along the seafront | Statement: [Blackpool Illuminations, primaryTransportExperience, driving or riding along the seafront]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTransportExperience Context triple: [Blackpool Illuminations, primaryTransportExperience, driving or riding along the seafront]
-
A.
primaryTransport
Indicates that one entity serves as the main or most commonly used means of transportation for another entity.
-
B.
primaryExperience
chosen
Indicates that one entity is the main or most significant experience associated with another entity, as opposed to secondary or supporting experiences.
-
C.
primaryTransports
Indicates that one entity serves as the main means or method of transporting or conveying another entity.
-
D.
hasRideExperience
Indicates that one entity has undergone, participated in, or possesses experience with a particular ride or riding activity in relation to another entity.
-
E.
primaryTransportModel
Indicates that one transport model is designated as the main or default model used for a given context or entity.
- 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_69f05b06807c81909b4bbd4c20403a2b |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_6a00868083b081909afc3d8d4ad56b43 |
completed | May 10, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_6a0084f5f72c8190b08afa82690e322a |
completed | May 10, 2026, 1:15 p.m. |
Created at: April 28, 2026, 7:35 a.m.