Triple
T21536681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Nothing |
E531366
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | ContentFilm |
—
|
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: ContentFilm | Statement: [Big Nothing, productionCompany, ContentFilm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ContentFilm Context triple: [Big Nothing, productionCompany, ContentFilm]
-
A.
ContentFilm
chosen
ContentFilm is a film production and distribution company known for backing independent and critically acclaimed movies such as "Thank You for Smoking."
-
B.
FilmFour
FilmFour is a British film production company and former television channel associated with Channel 4, known for backing distinctive independent and arthouse films.
-
C.
VideoFilmes
VideoFilmes is a Brazilian film production company known for its work on acclaimed art-house and independent films.
-
D.
FilmScene cinema
FilmScene cinema is an independent, nonprofit movie theater and film arts organization known for showcasing arthouse, foreign, and documentary films in Iowa City, Iowa.
-
E.
Flims
Flims is a Swiss alpine resort village in the canton of Graubünden, known for its skiing, hiking, and scenic mountain landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0e5a9c8190894ec3666d3296aa |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.