Triple
T28377164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey's Toontown Depot |
E718782
|
entity |
| Predicate | isThemedTo |
P164442
|
FINISHED |
| Object | a whimsical cartoon train station |
—
|
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: a whimsical cartoon train station | Statement: [Mickey's Toontown Depot, isThemedTo, a whimsical cartoon train station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isThemedTo Context triple: [Mickey's Toontown Depot, isThemedTo, a whimsical cartoon train station]
-
A.
usesThemeFrom
Indicates that one work incorporates, references, or is based on the thematic material of another work.
-
B.
usesThemeBy
Indicates that one entity incorporates, applies, or is based on a theme that was created, defined, or provided by another entity.
-
C.
reflectsOnTheme
Indicates that one entity critically considers, analyzes, or comments on the theme expressed or embodied by another entity.
-
D.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
E.
supportsThemeOf
Indicates that one entity reinforces, aligns with, or contributes to the central theme expressed by another entity.
- F. None of above. chosen
Provenance (4 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64c5eee988190aa18cd909ea3e855 |
completed | May 2, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69f641e2f1708190b45b48d6a43c51d2 |
completed | May 2, 2026, 6:26 p.m. |
| PDg | Predicate description generation | batch_69f64bca8574819095e081cbb7e2f369 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 28, 2026, 1:03 a.m.