Triple
T14396261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Aghassipour |
E356955
|
entity |
| Predicate | coFoundedWith |
P2835
|
FINISHED |
| Object | Mikkel Svane |
E356954
|
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: Mikkel Svane | Statement: [Alexander Aghassipour, coFoundedWith, Mikkel Svane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mikkel Svane Context triple: [Alexander Aghassipour, coFoundedWith, Mikkel Svane]
-
A.
Mikkel Svane
chosen
Mikkel Svane is a Danish entrepreneur best known as the co-founder and longtime CEO of the customer service software company Zendesk.
-
B.
Mikkel Bondesen
Mikkel Bondesen is a television producer known for his executive production work on series such as "The Comedians."
-
C.
Peter Høj
Peter Høj is an Australian academic and university leader who has served as vice-chancellor at several major universities, including the University of Adelaide.
-
D.
Jesper Nøhr
Jesper Nøhr is a Danish software developer and entrepreneur best known for creating the code hosting platform Bitbucket.
-
E.
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.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90826f908190b3969af9b7cf922f |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a36382481909a39ba5e51084051 |
completed | May 8, 2026, 5:52 a.m. |
Created at: April 10, 2026, 1:17 a.m.