Triple

T8145889
Position Surface form Disambiguated ID Type / Status
Subject Per Wästberg E190209 entity
Predicate notable work P4 FINISHED
Object Luftburen
Luftburen is a notable literary work by Swedish author Per Wästberg, reflecting his characteristic blend of social insight and nuanced psychological portrayal.
 E713150 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: Luftburen | Statement: [Per Wästberg, notable work, Luftburen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luftburen
Context triple: [Per Wästberg, notable work, Luftburen]
  • A. Luft
    Luft is a surname most notably associated with Sid Luft, the American film producer and third husband of entertainer Judy Garland.
  • B. Hufschlag
    Hufschlag is a small district of Traunstein in Bavaria, Germany, known as part of the rural setting where Pope Benedict XVI (Joseph Ratzinger) spent part of his childhood.
  • C. Avion
    Avion is a commune in the Pas-de-Calais department in northern France.
  • D. Barkhorn
    Barkhorn is a German surname most notably associated with Gerhard Barkhorn, one of the highest-scoring fighter aces in aviation history during World War II.
  • E. Bomber
    Bomber is the nickname and mascot representing the athletic teams of Ithaca College.
  • 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: Luftburen
Triple: [Per Wästberg, notable work, Luftburen]
Generated description
Luftburen is a notable literary work by Swedish author Per Wästberg, reflecting his characteristic blend of social insight and nuanced psychological portrayal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luftburen
Target entity description: Luftburen is a notable literary work by Swedish author Per Wästberg, reflecting his characteristic blend of social insight and nuanced psychological portrayal.
  • A. Luft
    Luft is a surname most notably associated with Sid Luft, the American film producer and third husband of entertainer Judy Garland.
  • B. Hufschlag
    Hufschlag is a small district of Traunstein in Bavaria, Germany, known as part of the rural setting where Pope Benedict XVI (Joseph Ratzinger) spent part of his childhood.
  • C. Avion
    Avion is a commune in the Pas-de-Calais department in northern France.
  • D. Barkhorn
    Barkhorn is a German surname most notably associated with Gerhard Barkhorn, one of the highest-scoring fighter aces in aviation history during World War II.
  • E. Bomber
    Bomber is the nickname and mascot representing the athletic teams of Ithaca College.
  • 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_69ca82be7ba8819087de0147e9292c83 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4447dbc48190affb0f34f6c85f5a completed March 31, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc94b0fc0481909a21f42364a92158 completed April 1, 2026, 3:44 a.m.
NEDg Description generation batch_69cc963fe2f8819098ad6a726e226189 completed April 1, 2026, 3:51 a.m.
NED2 Entity disambiguation (via description) batch_69cc977c9bf4819081c4df682e4cdf1e completed April 1, 2026, 3:56 a.m.
Created at: March 30, 2026, 5:36 p.m.