Triple
T30581472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N'Jadaka |
E778391
|
entity |
| Predicate | filmAdversaryOf |
P169875
|
FINISHED |
| Object | T'Challa |
—
|
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: T'Challa | Statement: [N'Jadaka, filmAdversaryOf, T'Challa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmAdversaryOf Context triple: [N'Jadaka, filmAdversaryOf, T'Challa]
-
A.
alliedWithInFilm
Indicates that two characters or entities are portrayed as allies or cooperating on the same side within the context of a specific film.
-
B.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
C.
performedInFilmOpposite
Indicates that two performers acted together in significant, often directly interacting roles in the same film.
-
D.
actúaEn
Indicates that an actor or performer takes part in or appears in a specific production, such as a film, play, or television show.
-
E.
businessPartnerInFilm
Indicates that two entities are business partners within the context of a specific film or film-related project.
- F. None of above. chosen
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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6894261048190aa19ffe41a34413c |
completed | May 2, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f6827a7b9c8190ab13605aacc81df9 |
completed | May 2, 2026, 11:02 p.m. |
Created at: April 29, 2026, 8:23 p.m.