Triple
T9733808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Magic Carpets of Aladdin |
E236007
|
entity |
| Predicate | queueAccessibility |
P80912
|
FINISHED |
| Object | accessible with limitations |
—
|
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: accessible with limitations | Statement: [The Magic Carpets of Aladdin, queueAccessibility, accessible with limitations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queueAccessibility Context triple: [The Magic Carpets of Aladdin, queueAccessibility, accessible with limitations]
-
A.
queueType
Indicates the classification or category of a queue that specifies how items in it are organized, prioritized, or processed.
-
B.
queueLocation
Indicates the place or position where an entity is arranged to wait in a queue or line.
-
C.
queueTypical
Indicates that an entity is in or follows a standard or commonly expected queueing order or behavior relative to others.
-
D.
accessibleOn
Indicates that one entity can be reached, used, or obtained through another entity (such as a platform, device, or medium).
-
E.
accessibilityFeatures
chosen
Indicates the specific tools, settings, or design elements provided to make something usable or understandable for people with disabilities or diverse access needs.
- 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.