Triple
T8070935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Claus, Indiana |
E188369
|
entity |
| Predicate | hasDecorations |
P38145
|
FINISHED |
| Object | year-round Christmas decorations |
—
|
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: year-round Christmas decorations | Statement: [Santa Claus, Indiana, hasDecorations, year-round Christmas decorations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDecorations Context triple: [Santa Claus, Indiana, hasDecorations, year-round Christmas decorations]
-
A.
hasDecor
chosen
Indicates that one entity possesses, features, or is adorned with a particular decorative element or style.
-
B.
hasCeilingDecoration
Indicates that an entity features or is adorned with a decorative element on its ceiling.
-
C.
relatedDecoration
Indicates that one decoration is associated with, complements, or is contextually linked to another decoration.
-
D.
decorationsReceived
Indicates that an entity has been awarded or has obtained one or more decorations, honors, or ceremonial adornments from another entity or source.
-
E.
typeOfDecoration
Indicates the specific kind or style of decoration associated with an entity or applied in a given context.
- 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_69ca82b42674819086840efea12478e5 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ffe29188190834ec4f71043a99d |
completed | March 31, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69cb049cd51c8190bb3b0f503e42fa8d |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:27 p.m.