Triple
T7843830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Majgull Axelsson |
E181869
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Majgull Axelsson |
E181869
|
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: Majgull Axelsson | Statement: [Majgull Axelsson, name, Majgull Axelsson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Majgull Axelsson Context triple: [Majgull Axelsson, name, Majgull Axelsson]
-
A.
Majgull Axelsson
chosen
Majgull Axelsson is a Swedish journalist and award-winning author known for her socially engaged novels that often explore themes of injustice and marginalized lives.
-
B.
Åsa Larsson
Åsa Larsson is a Swedish crime fiction author best known for her Rebecka Martinsson series set in northern Sweden.
-
C.
Marianne Dahlbäck
Marianne Dahlbäck is a Swedish architect best known for co-designing Stockholm’s Vasa Museum, one of Scandinavia’s most visited cultural landmarks.
-
D.
Maud Runnström
Maud Runnström was the wife of Swedish physicist and Nobel laureate Kai Siegbahn.
-
E.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb163c72248190b53bc53980e8ac0f |
completed | March 31, 2026, 12:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5ae9758c819091e270343ed289aa |
completed | March 31, 2026, 5:26 a.m. |
Created at: March 30, 2026, 4:48 p.m.