Triple
T23141564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sten Nilsson Bielke |
E577475
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Sten |
—
|
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: Sten | Statement: [Sten Nilsson Bielke, hasGivenName, Sten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sten Context triple: [Sten Nilsson Bielke, hasGivenName, Sten]
-
A.
Sten
chosen
Sten is a Scandinavian male given name of Old Norse origin, commonly associated with Sweden and meaning "stone."
-
B.
Steng
Steng is the family name of Austrian actor and director Klaus Maria Brandauer, known for his acclaimed performances in European cinema and Hollywood films.
-
C.
Stig
Stig is a Scandinavian male given name commonly used in Sweden and other Nordic countries.
-
D.
Stig
Stig is a historical region in eastern Serbia known for its fertile plains and agricultural significance.
-
E.
Stange
Stange is a rural municipality in Innlandet county, Norway, known for its agricultural landscape and proximity to the town of Hamar.
- 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_69e245f8e6248190ba3d58e068b4dccb |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18eca8a9081908dcc39409f615b7c |
completed | April 29, 2026, 4:53 a.m. |
Created at: April 17, 2026, 4 p.m.