Triple

T7651021
Position Surface form Disambiguated ID Type / Status
Subject Hannes Alfvén E173250 entity
Predicate familyName P18 FINISHED
Object Alfvén
Alfvén is a Swedish surname most notably associated with Hannes Alfvén, the Nobel Prize–winning physicist who pioneered the field of magnetohydrodynamics.
 E679638 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: Alfvén | Statement: [Hannes Alfvén, familyName, Alfvén]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alfvén
Context triple: [Hannes Alfvén, familyName, Alfvén]
  • A. Norrström
    Norrström is a short but significant river in central Stockholm that connects Lake Mälaren with the Baltic Sea and flows past several of the city’s key historic and governmental buildings.
  • B. Alfredson
    Alfredson is a Swedish surname most notably associated with filmmaker Tomas Alfredson.
  • C. Sólfar
    Sólfar is a famous stainless-steel sculpture in Reykjavík, Iceland, depicting a stylized Viking ship and symbolizing dreams of discovery and freedom.
  • D. Álfur
    Álfur was a medieval Roman Catholic bishop who served in the historic Diocese of Garðar in Greenland.
  • E. Alvik
    Alvik is a district in western Stockholm known as a key public transport hub, particularly for its tram and metro connections.
  • 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: Alfvén
Triple: [Hannes Alfvén, familyName, Alfvén]
Generated description
Alfvén is a Swedish surname most notably associated with Hannes Alfvén, the Nobel Prize–winning physicist who pioneered the field of magnetohydrodynamics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alfvén
Target entity description: Alfvén is a Swedish surname most notably associated with Hannes Alfvén, the Nobel Prize–winning physicist who pioneered the field of magnetohydrodynamics.
  • A. Norrström
    Norrström is a short but significant river in central Stockholm that connects Lake Mälaren with the Baltic Sea and flows past several of the city’s key historic and governmental buildings.
  • B. Alfredson
    Alfredson is a Swedish surname most notably associated with filmmaker Tomas Alfredson.
  • C. Sólfar
    Sólfar is a famous stainless-steel sculpture in Reykjavík, Iceland, depicting a stylized Viking ship and symbolizing dreams of discovery and freedom.
  • D. Álfur
    Álfur was a medieval Roman Catholic bishop who served in the historic Diocese of Garðar in Greenland.
  • E. Alvik
    Alvik is a district in western Stockholm known as a key public transport hub, particularly for its tram and metro connections.
  • 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_69c70175e4b88190bc40c839a42180d4 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89ae293148190a30ef03a4a594fe6 completed March 29, 2026, 3:22 a.m.
NEDg Description generation batch_69c89d2e42fc81908b1ddeb0375b47c8 completed March 29, 2026, 3:31 a.m.
NED2 Entity disambiguation (via description) batch_69c89d9255e08190b248f0c3fc858bc5 completed March 29, 2026, 3:33 a.m.
Created at: March 27, 2026, 3:58 p.m.