Triple
T19095475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Royal Affair |
E467392
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Kasper Leick
Kasper Leick is a film editor known for his work on the historical drama "A Royal Affair."
|
E1357963
|
NE FINISHED |
How this triple was built (4 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: Kasper Leick | Statement: [A Royal Affair, editedBy, Kasper Leick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kasper Leick Context triple: [A Royal Affair, editedBy, Kasper Leick]
-
A.
Kasper Winding
Kasper Winding is a Danish composer, producer, and musician known for his work on film scores, pop music, and various international collaborations.
-
B.
Jesper Winge Leisner
Jesper Winge Leisner is a Danish composer and musician known for his work in film, television, and theater music.
-
C.
Rasmus Heisterberg
Rasmus Heisterberg is a Danish screenwriter and filmmaker known for his work on acclaimed Nordic crime thrillers and literary adaptations.
-
D.
Anders Gyldenklou
Anders Gyldenklou was a Swedish nobleman and statesman who rose to one of the highest financial and political offices in the Swedish realm.
-
E.
Christoffer Reedtz
Christoffer Reedtz is a Danish businessman and football data analyst best known as the owner of English football club Notts County.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kasper Leick Triple: [A Royal Affair, editedBy, Kasper Leick]
Generated description
Kasper Leick is a film editor known for his work on the historical drama "A Royal Affair."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kasper Leick Target entity description: Kasper Leick is a film editor known for his work on the historical drama "A Royal Affair."
-
A.
Kasper Winding
Kasper Winding is a Danish composer, producer, and musician known for his work on film scores, pop music, and various international collaborations.
-
B.
Jesper Winge Leisner
Jesper Winge Leisner is a Danish composer and musician known for his work in film, television, and theater music.
-
C.
Rasmus Heisterberg
Rasmus Heisterberg is a Danish screenwriter and filmmaker known for his work on acclaimed Nordic crime thrillers and literary adaptations.
-
D.
Anders Gyldenklou
Anders Gyldenklou was a Swedish nobleman and statesman who rose to one of the highest financial and political offices in the Swedish realm.
-
E.
Christoffer Reedtz
Christoffer Reedtz is a Danish businessman and football data analyst best known as the owner of English football club Notts County.
- F. None of above. chosen
Provenance (5 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e368f20c8190bd84d2ba320991ac |
completed | April 20, 2026, 8:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05dd96b8b48190a3c5b14122380b68 |
completed | May 14, 2026, 2:35 p.m. |
| NEDg | Description generation | batch_6a05dfcd85b08190b0ec431590396dbb |
completed | May 14, 2026, 2:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05e09c58308190975c69c86482292a |
completed | May 14, 2026, 2:47 p.m. |
Created at: April 10, 2026, 12:04 p.m.