Triple
T28722017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freddy Freeman (Shazam! 2019 film) |
E730120
|
entity |
| Predicate | roomDecoratedWith |
P8228
|
FINISHED |
| Object | superhero posters |
—
|
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: superhero posters | Statement: [Freddy Freeman (Shazam! 2019 film), roomDecoratedWith, superhero posters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roomDecoratedWith Context triple: [Freddy Freeman (Shazam! 2019 film), roomDecoratedWith, superhero posters]
-
A.
interiorDecoratedBy
Indicates that the interior of a space or structure has been designed or decorated by a specific agent or entity.
-
B.
decoration
Indicates that one entity serves as an ornament or embellishing element for another entity, enhancing its appearance or style.
-
C.
decorationCategory
Indicates the classification or type of decoration that an item, element, or space belongs to.
-
D.
decorations
chosen
Indicates that one entity adds, provides, or serves as ornamental or decorative elements for another entity.
-
E.
decorativeCategory
Indicates that one entity is classified as belonging to a particular decorative style, theme, or ornamentation category of another entity.
- 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f657099ccc8190a2b92a395f5436e7 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 5:54 a.m.