Triple
T19760907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parques Reunidos |
E474624
|
entity |
| Predicate | owns |
P347
|
FINISHED |
| Object | Story Land |
—
|
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: Story Land | Statement: [Parques Reunidos, owns, Story Land]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Story Land Context triple: [Parques Reunidos, owns, Story Land]
-
A.
Story Land
chosen
Story Land is a family-oriented theme park in Bartlett, New Hampshire, featuring storybook- and fairy tale–themed rides and attractions for young children.
-
B.
Storybook Land
Storybook Land is a fairy tale–themed amusement park in Aberdeen, South Dakota, featuring storybook characters, themed rides, and attractions for young children and families.
-
C.
Adventure Land
Adventure Land is a themed area within Europa-Park that immerses visitors in adventurous, exploration-inspired settings and attractions.
-
D.
Discoveryland
Discoveryland is a retro-futuristic themed land at Disneyland Paris inspired by the visionary works of Jules Verne and classic science fiction.
-
E.
Loompaland
Loompaland is the remote, fictional homeland of the Oompa-Loompas in Roald Dahl’s Willy Wonka stories.
- 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.