Triple
T19760908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parques Reunidos |
E474624
|
entity |
| Predicate | owns |
P347
|
FINISHED |
| Object | Dutch Wonderland |
—
|
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: Dutch Wonderland | Statement: [Parques Reunidos, owns, Dutch Wonderland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dutch Wonderland Context triple: [Parques Reunidos, owns, Dutch Wonderland]
-
A.
Dutch Wonderland
chosen
Dutch Wonderland is a family-oriented amusement park in Lancaster, Pennsylvania, known for its kid-friendly rides, attractions, and castle-themed setting.
-
B.
Bobbejaanland
Bobbejaanland is a Belgian theme park known for its family-friendly attractions, roller coasters, and live entertainment.
-
C.
Efteling
Efteling is a major Dutch fantasy-themed amusement park and resort known for its fairy-tale attractions and immersive storytelling.
-
D.
Keukenhof
Keukenhof is one of the world’s largest and most famous flower gardens in the Netherlands, renowned for its spectacular spring displays of tulips and other bulb flowers.
-
E.
Kennispark Twente
Kennispark Twente is an innovation and business park in Enschede, the Netherlands, focused on fostering high-tech startups and knowledge-intensive companies in close collaboration with the University of Twente.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6531f38b48190b1663870a8da5a59 |
completed | April 20, 2026, 4:23 p.m. |
Created at: April 10, 2026, 1:48 p.m.