Triple
T22039472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Greenwood |
E544300
|
entity |
| Predicate | workedOn |
P3
|
FINISHED |
| Object | Darkest Hour (2017 film) |
—
|
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: Darkest Hour (2017 film) | Statement: [Sarah Greenwood, workedOn, Darkest Hour (2017 film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darkest Hour (2017 film) Context triple: [Sarah Greenwood, workedOn, Darkest Hour (2017 film)]
-
A.
Darkest Hour
chosen
Darkest Hour is a 2017 historical drama film depicting Winston Churchill’s early days as British Prime Minister during World War II, starring Gary Oldman in an Oscar-winning performance.
-
B.
Darkest Hour
Darkest Hour is an American metal band known for blending melodic death metal and hardcore punk influences into an aggressive, politically charged sound.
-
C.
The Darkest Hour
The Darkest Hour is a silent-era film produced by the early American motion picture studio Vitagraph Company of America.
-
D.
The Darkest Hour
The Darkest Hour is a 2011 science fiction thriller film about a group of young people in Moscow fighting to survive an invisible alien invasion that drains electrical energy.
-
E.
Dunkirk
Dunkirk is a coastal town in northern France best known as the site of the World War II evacuation of Allied troops in 1940.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127f532b08190be80c5af039b4c29 |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:25 p.m.