Triple
T7482768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ylva Johansson |
E176801
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ylva Johansson |
E176801
|
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: Ylva Johansson | Statement: [Ylva Johansson, name, Ylva Johansson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ylva Johansson Context triple: [Ylva Johansson, name, Ylva Johansson]
-
A.
Ylva Johansson
chosen
Ylva Johansson is a Swedish politician who has served as European Commissioner for Home Affairs and previously held several ministerial posts in the Swedish government.
-
B.
Åsa Larsson
Åsa Larsson is a Swedish crime fiction author best known for her Rebecka Martinsson series set in northern Sweden.
-
C.
Anna-Lisa Hansson
Anna-Lisa Hansson was a daughter of Swedish Prime Minister Per Albin Hansson and a member of his prominent political family.
-
D.
Ellen Lundström
Ellen Lundström was the first wife of renowned Swedish film director Ingmar Bergman, with whom he had several children before their divorce.
-
E.
Hanna Alström
Hanna Alström is a Swedish actress best known internationally for her role as Princess Tilde in the action-comedy film "Kingsman: The Secret Service" and its sequel.
- 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_69c69f24ac508190bb98fe927c0bd065 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5374bb08190bdf6ca72a3d0cd1c |
completed | March 27, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c68bcf081908a2c280152d887f0 |
completed | March 28, 2026, 8:39 p.m. |
Created at: March 27, 2026, 3:42 p.m.