Triple
T2556651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janus Friis |
E56743
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Janus Friis |
E56743
|
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: Janus Friis | Statement: [Janus Friis, name, Janus Friis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Janus Friis Context triple: [Janus Friis, name, Janus Friis]
-
A.
Janus Friis
chosen
Janus Friis is a Danish entrepreneur best known for co-founding the internet communications platform Skype.
-
B.
Nikolaj Bjørner
Nikolaj Bjørner is a computer scientist best known for his work on automated theorem proving and the development of the Z3 SMT solver.
-
C.
Mikkel E. G. Nielsen
Mikkel E. G. Nielsen is a Danish film editor known for his work on acclaimed international films, including the war drama "Beasts of No Nation."
-
D.
Jens Blauert
Jens Blauert is a German acoustician renowned for his pioneering work in spatial hearing and psychoacoustics.
-
E.
Christian Hansen
Christian Hansen was a German general in the Wehrmacht during World War II who held high-level field commands on the Eastern Front.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd310b3a48190b275be13eb050e57 |
completed | March 7, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5d1d937c8190ac6b7bb405a49c3c |
completed | March 9, 2026, 11:51 p.m. |
Created at: March 6, 2026, 9:48 p.m.