Triple
T19092162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roland Møller |
E467313
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Roland Møller |
—
|
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: Roland Møller | Statement: [Roland Møller, name, Roland Møller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roland Møller Context triple: [Roland Møller, name, Roland Møller]
-
A.
Roland Møller
chosen
Roland Møller is a Danish actor and former rapper known for his intense supporting roles in films such as "Land of Mine," "Atomic Blonde," and "Papillon."
-
B.
Christian Møller
Christian Møller was a Danish theoretical physicist known for his contributions to quantum electrodynamics and the theory of relativity.
-
C.
Morten Ristorp
Morten Ristorp is a Danish songwriter and producer known for his work on international pop and R&B hits.
-
D.
Jens Toldstrup
Jens Toldstrup was a prominent Danish resistance leader during World War II, known for organizing sabotage and intelligence operations against the German occupation.
-
E.
Flemming Ørnskov
Flemming Ørnskov is a Danish physician and business executive best known for serving as CEO of the rare-disease biopharmaceutical company Shire plc.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e34c22a08190bf34f92f727268c5 |
completed | April 20, 2026, 8:26 a.m. |
Created at: April 10, 2026, 12:04 p.m.