Triple
T7651664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bo Lundgren |
E173266
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lundgren
Lundgren is a Swedish surname borne by various notable individuals in fields such as politics, sports, and entertainment.
|
E680273
|
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: Lundgren | Statement: [Bo Lundgren, familyName, Lundgren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lundgren Context triple: [Bo Lundgren, familyName, Lundgren]
-
A.
Bo Lundgren
Bo Lundgren is a Swedish politician and former leader of the Moderate Party who also served as Sweden’s Minister for Fiscal and Financial Affairs.
-
B.
Kim Lundgren
Kim Lundgren is an entrepreneur best known as one of the founders behind the German airline Air Berlin.
-
C.
Lundh
Lundh is a variant form of the Scandinavian surname Lund, which is associated with families originating from regions such as Sweden and Denmark.
-
D.
Skarsgård
Skarsgård is a prominent Swedish acting family name associated with several internationally recognized film and television performers.
-
E.
Hedlund
Hedlund is a surname most notably associated with American actor Garrett Hedlund, known for roles in films like "Tron: Legacy" and "Friday Night Lights."
- 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: Lundgren Triple: [Bo Lundgren, familyName, Lundgren]
Generated description
Lundgren is a Swedish surname borne by various notable individuals in fields such as politics, sports, and entertainment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lundgren Target entity description: Lundgren is a Swedish surname borne by various notable individuals in fields such as politics, sports, and entertainment.
-
A.
Bo Lundgren
Bo Lundgren is a Swedish politician and former leader of the Moderate Party who also served as Sweden’s Minister for Fiscal and Financial Affairs.
-
B.
Kim Lundgren
Kim Lundgren is an entrepreneur best known as one of the founders behind the German airline Air Berlin.
-
C.
Lundh
Lundh is a variant form of the Scandinavian surname Lund, which is associated with families originating from regions such as Sweden and Denmark.
-
D.
Skarsgård
Skarsgård is a prominent Swedish acting family name associated with several internationally recognized film and television performers.
-
E.
Hedlund
Hedlund is a surname most notably associated with American actor Garrett Hedlund, known for roles in films like "Tron: Legacy" and "Friday Night Lights."
- 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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701770ac881909452348c9547ab47 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89aeb66c081909f3a3d6385637c25 |
completed | March 29, 2026, 3:22 a.m. |
| NEDg | Description generation | batch_69c89ed393648190a32cf9267968faf5 |
completed | March 29, 2026, 3:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c89f35a7488190a6a9bc3d10bedd5a |
completed | March 29, 2026, 3:40 a.m. |
Created at: March 27, 2026, 3:58 p.m.