Triple
T34680805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Kiss at the End of the Rainbow |
E890617
|
entity |
| Predicate | fictionalDuoInFilm |
P34570
|
FINISHED |
| Object | Mitch & Mickey |
—
|
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: Mitch & Mickey | Statement: [A Kiss at the End of the Rainbow, fictionalDuoInFilm, Mitch & Mickey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalDuoInFilm Context triple: [A Kiss at the End of the Rainbow, fictionalDuoInFilm, Mitch & Mickey]
-
A.
performedInFilmOpposite
Indicates that two performers acted together in significant, often directly interacting roles in the same film.
-
B.
isFictionalTwinOf
Indicates that one entity is the imagined or fictional twin counterpart of another entity, typically within a narrative or creative context.
-
C.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
D.
fictionalRelationship
chosen
Indicates a relationship that exists only within a fictional or imagined context between entities.
-
E.
hasTwinActors
Indicates that two or more actors share a twin relationship, typically portraying twin characters or being treated as twins within 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_69f349dabc008190a18999c26682ed47 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fecb4d02f881909a9ee97ce98000d5 |
completed | May 9, 2026, 5:51 a.m. |
| PD | Predicate disambiguation | batch_69fec9846c1c8190b317f0711f0755db |
completed | May 9, 2026, 5:43 a.m. |
Created at: May 1, 2026, 2:05 a.m.