Triple
T7843832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Majgull Axelsson |
E181869
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Axelsson
Axelsson is a common Swedish surname borne by various notable individuals in fields such as literature, sports, and politics.
|
E699004
|
NE FINISHED |
How this triple was built (4 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: Axelsson | Statement: [Majgull Axelsson, familyName, Axelsson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Axelsson Context triple: [Majgull Axelsson, familyName, Axelsson]
-
A.
Axel
Axel is a child associated with Nairobi, a character from the Spanish television series "Money Heist" (La Casa de Papel).
-
B.
Axel
Axel is a given name associated with the Finnish painter Akseli Gallen-Kallela, renowned for his depictions of the Kalevala and contributions to Finnish national romantic art.
-
C.
Axel Milberg
Axel Milberg is a German actor known for his extensive work in film and television, including prominent roles in dramas and crime series.
-
D.
Åkerlund
Åkerlund is a Swedish surname most notably associated with acclaimed music video and film director Jonas Åkerlund.
-
E.
Matthew Axelson
Matthew Axelson was a United States Navy SEAL petty officer who fought and was killed during the ill-fated Operation Red Wings in Afghanistan, later portrayed in the film "Lone Survivor."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Axelsson Triple: [Majgull Axelsson, familyName, Axelsson]
Generated description
Axelsson is a common Swedish surname borne by various notable individuals in fields such as literature, sports, and politics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Axelsson Target entity description: Axelsson is a common Swedish surname borne by various notable individuals in fields such as literature, sports, and politics.
-
A.
Axel
Axel is a child associated with Nairobi, a character from the Spanish television series "Money Heist" (La Casa de Papel).
-
B.
Axel
Axel is a given name associated with the Finnish painter Akseli Gallen-Kallela, renowned for his depictions of the Kalevala and contributions to Finnish national romantic art.
-
C.
Axel Milberg
Axel Milberg is a German actor known for his extensive work in film and television, including prominent roles in dramas and crime series.
-
D.
Åkerlund
Åkerlund is a Swedish surname most notably associated with acclaimed music video and film director Jonas Åkerlund.
-
E.
Matthew Axelson
Matthew Axelson was a United States Navy SEAL petty officer who fought and was killed during the ill-fated Operation Red Wings in Afghanistan, later portrayed in the film "Lone Survivor."
- F. None of above. chosen
Provenance (5 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. |
| NEDg | Description generation | batch_69cb762dd8348190bf74be4e7f5df1e7 |
completed | March 31, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cbb24068908190977b266366e5ceea |
completed | March 31, 2026, 11:38 a.m. |
Created at: March 30, 2026, 4:48 p.m.