Triple
T9733797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Magic Carpets of Aladdin |
E236007
|
entity |
| Predicate | photoPolicy |
P42843
|
FINISHED |
| Object | on-ride photography allowed |
—
|
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: on-ride photography allowed | Statement: [The Magic Carpets of Aladdin, photoPolicy, on-ride photography allowed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photoPolicy Context triple: [The Magic Carpets of Aladdin, photoPolicy, on-ride photography allowed]
-
A.
allowsPhotography
chosen
Indicates that one entity permits another entity to take photographs in a particular context or location.
-
B.
hasPhotographyRestrictions
Indicates that there are specific rules or limitations governing whether and how photography is allowed.
-
C.
mediaPolicy
Indicates a relationship where an entity defines or is governed by rules and guidelines for creating, using, or managing media content.
-
D.
collectionPolicy
Indicates the rules or guidelines that govern how items are gathered, selected, and managed within a collection.
-
E.
boardingPolicy
Indicates the rules or procedures governing how and in what order passengers are allowed to board a vehicle or vessel.
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9eb54fe481908b0202f104b75dc1 |
completed | April 1, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69cd03c6ffc88190a5e9569e19122ad5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:22 p.m.