Triple
T35920695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario + Rabbids Kingdom Battle |
E1038874
|
entity |
| Predicate | hasNonPlayableCameo |
P108137
|
FINISHED |
| Object | Wendy O. Koopa |
E320118
|
NE 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: Wendy O. Koopa | Statement: [Mario + Rabbids Kingdom Battle, hasNonPlayableCameo, Wendy O. Koopa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNonPlayableCameo Context triple: [Mario + Rabbids Kingdom Battle, hasNonPlayableCameo, Wendy O. Koopa]
-
A.
cameoCharacter
chosen
Indicates that one entity appears briefly or in a minor, special-guest role within the context or work associated with another entity.
-
B.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
C.
franchiseCameo
Indicates that an entity makes a brief appearance or reference within a work that belongs to a particular franchise or series.
-
D.
appearsWithCharacter
Indicates that two characters are shown or present together within the same scene, shot, or context.
-
E.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
- F. None of above.
Provenance (4 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3c170c1ecc8190961cc5ed8210f6be |
completed | June 24, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.