Triple
T29957064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boom, Belgium |
E760928
|
entity |
| Predicate | TomorrowlandLocation |
P168298
|
FINISHED |
| Object | De Schorre recreation area |
—
|
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: De Schorre recreation area | Statement: [Boom, Belgium, TomorrowlandLocation, De Schorre recreation area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: TomorrowlandLocation Context triple: [Boom, Belgium, TomorrowlandLocation, De Schorre recreation area]
-
A.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
B.
placeOfFictionalEvent
Indicates the location where a fictional event is depicted as occurring within a narrative or story.
-
C.
themeParkAttractionLocation
Indicates the specific place or area within a theme park where a particular attraction is situated.
-
D.
placeOfFictionalActivity
Indicates the location or setting where a fictional event, action, or storyline takes place.
-
E.
locatedOnFictionalRoute
Indicates that something is situated along or associated with a route that exists only within a fictional or imaginary setting.
- 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_69f22466327481908ba6db916837bece |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6783b53048190860ff2712bc96891 |
completed | May 2, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 29, 2026, 6:27 p.m.