Triple
T20558354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet (2019 film) |
E504778
|
entity |
| Predicate | distributedBy |
P1951
|
FINISHED |
| Object | Focus Features |
—
|
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: Focus Features | Statement: [Harriet (2019 film), distributedBy, Focus Features]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Focus Features Context triple: [Harriet (2019 film), distributedBy, Focus Features]
-
A.
Focus Features
chosen
Focus Features is an American film production and distribution company known for releasing critically acclaimed independent and art-house movies.
-
B.
Feel Films
Feel Films is a British film and television production company known for producing high-quality literary and genre adaptations.
-
C.
Beyond Films
Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
-
D.
Marché du Film
Marché du Film is the Cannes Film Festival’s major international film market, where industry professionals buy, sell, and promote films and projects.
-
E.
Direct Cinema
Direct Cinema is a documentary filmmaking movement characterized by unobtrusive, observational techniques that aim to capture reality as it unfolds without scripted narration or interference.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5df84088190848c7eb35564d8f9 |
completed | April 20, 2026, 10:17 p.m. |
Created at: April 16, 2026, 11:38 a.m.