Triple
T12660300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Dane |
E302404
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Rasmus |
E452776
|
NE FINISHED |
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 | Statement: [Karl Dane, givenName, Rasmus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rasmus Context triple: [Karl Dane, givenName, Rasmus]
-
A.
Rasmus
chosen
Rasmus is a masculine given name of Scandinavian origin, commonly used in countries such as Denmark, Norway, and Sweden.
-
B.
Rasmus Hedegaard
Rasmus Hedegaard is a Danish DJ and music producer known for his electronic and pop-oriented remixes and collaborations.
-
C.
Niklas
Niklas is a masculine given name commonly used in Germanic and Scandinavian countries, derived from the Greek name Nikolaos.
-
D.
Rasmus Christensen
Rasmus Christensen is a Danish professional footballer known for playing as a defender in European club competitions.
-
E.
Jesper Rasmussen
Jesper Rasmussen is a Danish professional footballer known for playing as a forward in Denmark’s top leagues.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f66885e44c8190a650301b0e86d0f4 |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:19 p.m.