Triple
T34727522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christmas on Earth Continued (related projects and screenings) |
E1001110
|
entity |
| Predicate | recontextualizes |
P78725
|
FINISHED |
| Object | Christmas on Earth |
—
|
NE NERFINISHED |
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: Christmas on Earth | Statement: [Christmas on Earth Continued (related projects and screenings), recontextualizes, Christmas on Earth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recontextualizes Context triple: [Christmas on Earth Continued (related projects and screenings), recontextualizes, Christmas on Earth]
-
A.
recontextualizesStoriesFrom
Indicates that one entity takes stories originating from another entity and presents or interprets them in a new or altered context.
-
B.
reconstructs
Indicates performing an action to rebuild, restore, or reassemble something from its parts, damage, or prior state.
-
C.
reimagines
chosen
Indicates that one entity creatively reconceives, interprets, or presents another in a significantly new or different way.
-
D.
recreated
Indicates that an entity has been created again or restored, typically after being removed, destroyed, or significantly altered.
-
E.
recutIn
Indicates that an item has been cut again or re-edited into a new version, typically after an initial cutting or editing process.
- 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_69f76daeb6e48190a4c9a6b0edc80f72 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.