Triple
T6277761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All I Want for Christmas Is You (2019 Make My Wish Come True edition) |
E140703
|
entity |
| Predicate | featuresVisuals |
P29429
|
FINISHED |
| Object | festive storytelling |
—
|
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: festive storytelling | Statement: [All I Want for Christmas Is You (2019 Make My Wish Come True edition), featuresVisuals, festive storytelling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresVisuals Context triple: [All I Want for Christmas Is You (2019 Make My Wish Come True edition), featuresVisuals, festive storytelling]
-
A.
featuresDecor
Indicates that one entity includes or showcases the decor elements provided or defined by another entity.
-
B.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
C.
featuresReimaginedVersionOf
Indicates that something includes or presents a newly interpreted or updated version of another existing work or element.
-
D.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
-
E.
visualElements
chosen
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with 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_69c008cc158881908df6ec94a911c736 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063daec108190859d1d5dbafd5b42 |
completed | March 22, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69c05608a5608190b22a1fdc4060470d |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:26 p.m.