Triple
T22973871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 12 Strong |
E571259
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Rasmus Videbæk |
—
|
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: Rasmus Videbæk | Statement: [12 Strong, cinematographyBy, Rasmus Videbæk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rasmus Videbæk Context triple: [12 Strong, cinematographyBy, Rasmus Videbæk]
-
A.
Rasmus Videbæk
chosen
Rasmus Videbæk is a Danish cinematographer known for his work on international films and television, including the 2017 adaptation of Stephen King’s "The Dark Tower."
-
B.
Rasmus Christensen
Rasmus Christensen is a Danish professional footballer known for playing as a defender in European club competitions.
-
C.
Rasmus Hedegaard
Rasmus Hedegaard is a Danish DJ and music producer known for his electronic and pop-oriented remixes and collaborations.
-
D.
Erik Brøndum
Erik Brøndum was a Danish innkeeper and merchant in Skagen, best known as the father of painter Anna Ancher and as a central figure in the artistic milieu around Brøndum's Hotel.
-
E.
Rasmus Heisterberg
Rasmus Heisterberg is a Danish screenwriter and filmmaker known for his work on acclaimed Nordic crime thrillers and literary adaptations.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182350b448190a34e5fa0167fd964 |
completed | April 29, 2026, 3:59 a.m. |
Created at: April 17, 2026, 3:48 p.m.