Triple
T2528239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanna Alström |
E56089
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Alström
Alström is a Swedish surname borne by individuals such as actress Hanna Alström.
|
E274723
|
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: Alström | Statement: [Hanna Alström, familyName, Alström]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alström Context triple: [Hanna Alström, familyName, Alström]
-
A.
Ahlström
Ahlström is a Finnish industrial and design-oriented company known for its collaborations with prominent designers and its production of high-quality materials and products.
-
B.
Hansen
Hansen is a common Scandinavian-origin surname borne by numerous notable individuals across fields such as sports, politics, science, and the arts.
-
C.
Wolthusen
Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
-
D.
Larsen
Larsen is a surname of Scandinavian origin borne by numerous notable individuals across fields such as literature, music, and sports.
-
E.
Edelmann
Edelmann is a surname of German origin borne by various individuals across fields such as music, sports, and academia.
- 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: Alström Triple: [Hanna Alström, familyName, Alström]
Generated description
Alström is a Swedish surname borne by individuals such as actress Hanna Alström.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alström Target entity description: Alström is a Swedish surname borne by individuals such as actress Hanna Alström.
-
A.
Ahlström
Ahlström is a Finnish industrial and design-oriented company known for its collaborations with prominent designers and its production of high-quality materials and products.
-
B.
Hansen
Hansen is a common Scandinavian-origin surname borne by numerous notable individuals across fields such as sports, politics, science, and the arts.
-
C.
Wolthusen
Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
-
D.
Larsen
Larsen is a surname of Scandinavian origin borne by numerous notable individuals across fields such as literature, music, and sports.
-
E.
Edelmann
Edelmann is a surname of German origin borne by various individuals across fields such as music, sports, and academia.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd257ea908190a010c0b785853546 |
completed | March 7, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2bb3b55c81909e72ed055887ecca |
completed | March 9, 2026, 8:21 p.m. |
| NEDg | Description generation | batch_69af41aa199c8190b4478a93c41ae18a |
completed | March 9, 2026, 9:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af4277601c8190b55d5c5504dcd0ab |
completed | March 9, 2026, 9:58 p.m. |
Created at: March 6, 2026, 9:46 p.m.