Triple
T38132477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Smiler |
E952259
|
entity |
| Predicate | hasQueueLineTheming |
P164442
|
FINISHED |
| Object | psychological experiments |
—
|
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: psychological experiments | Statement: [The Smiler, hasQueueLineTheming, psychological experiments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQueueLineTheming Context triple: [The Smiler, hasQueueLineTheming, psychological experiments]
-
A.
queueAreaTheme
Indicates the thematic style or concept applied to the area where people wait in line for an attraction or service.
-
B.
isThemedTo
chosen
Indicates that one entity is designed, styled, or conceptually based around the subject, motif, or theme represented by another entity.
-
C.
queueStyle
Indicates the manner or configuration in which items or entities are ordered and processed within a queue.
-
D.
hasQueueAccessibility
Indicates that an entity provides accessible features or accommodations for people with disabilities in its queuing or waiting areas.
-
E.
hasFrontLineFeature
Indicates that an entity possesses a specific characteristic or element located on its front side or leading edge.
- 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_69f76f083548819082bd2bbf53c79e8e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:21 p.m.