Triple
T30581470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N'Jadaka |
E778391
|
entity |
| Predicate | filmBackground |
P169874
|
FINISHED |
| Object | former U.S. black-ops soldier |
—
|
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: former U.S. black-ops soldier | Statement: [N'Jadaka, filmBackground, former U.S. black-ops soldier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmBackground Context triple: [N'Jadaka, filmBackground, former U.S. black-ops soldier]
-
A.
filmHistory
Indicates that there is a historical or background connection between a film and another entity, such as its development, production, or past events related to it.
-
B.
filmBase
Indicates the primary location or headquarters from which a film-related entity (such as a production, company, or operation) is based or operates.
-
C.
filmContent
Indicates that one entity is the substantive material or subject matter contained within a film.
-
D.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
-
E.
backedFilm
Indicates that one entity provided financial or promotional support for the production or distribution of a film.
- 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.