Triple
T28980624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filey Bay |
E734537
|
entity |
| Predicate | hasNearbyHolidayPark |
P195581
|
FINISHED |
| Object | Primrose Valley Holiday Park |
—
|
NE NERFINISHED |
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: Primrose Valley Holiday Park | Statement: [Filey Bay, hasNearbyHolidayPark, Primrose Valley Holiday Park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyHolidayPark Context triple: [Filey Bay, hasNearbyHolidayPark, Primrose Valley Holiday Park]
-
A.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
B.
hasNearbyIslandPark
Indicates that an island park is located close to the referenced place or entity.
-
C.
hasNearbyStatePark
Indicates that a location is situated close to at least one designated state park.
-
D.
hasNearbyProvincialPark
Indicates that one entity is located close to, or in the vicinity of, a provincial park.
-
E.
hasNearbyHotel
Indicates that one entity is located close to or within a short distance of a hotel.
- F. None of above. chosen
Provenance (4 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_69f05b0dd9b481908b7901e1c95ff6b2 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69fddac42c4081908568649058e86458 |
completed | May 8, 2026, 12:44 p.m. |
Created at: April 28, 2026, 9:11 a.m.