Triple

T9979100
Position Surface form Disambiguated ID Type / Status
Subject Bücker Bü 131 E196403 entity
Predicate nicknamed P744 FINISHED
Object Jungmann
Jungmann is the nickname of the Bücker Bü 131, a German 1930s biplane widely used as a primary trainer aircraft before and during World War II.
 E834077 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: Jungmann | Statement: [Bücker Bü 131, nicknamed, Jungmann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jungmann
Context triple: [Bücker Bü 131, nicknamed, Jungmann]
  • A. Vogelmann
    Vogelmann is a German-language surname, likely originating as an occupational or descriptive name related to birds.
  • B. Klostermann
    Klostermann is a German academic publishing house known for its influential works in philosophy and the humanities.
  • C. Stahlecker
    Stahlecker is a German-language surname most notably associated with Franz Walter Stahlecker, a high-ranking SS officer and Nazi official during World War II.
  • D. Bischoffen
    Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
  • E. Sonnemann
    Sonnemann is the maiden surname of Emmy Göring, the German actress who became the second wife of Nazi leader Hermann Göring.
  • 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: Jungmann
Triple: [Bücker Bü 131, nicknamed, Jungmann]
Generated description
Jungmann is the nickname of the Bücker Bü 131, a German 1930s biplane widely used as a primary trainer aircraft before and during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jungmann
Target entity description: Jungmann is the nickname of the Bücker Bü 131, a German 1930s biplane widely used as a primary trainer aircraft before and during World War II.
  • A. Vogelmann
    Vogelmann is a German-language surname, likely originating as an occupational or descriptive name related to birds.
  • B. Klostermann
    Klostermann is a German academic publishing house known for its influential works in philosophy and the humanities.
  • C. Stahlecker
    Stahlecker is a German-language surname most notably associated with Franz Walter Stahlecker, a high-ranking SS officer and Nazi official during World War II.
  • D. Bischoffen
    Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
  • E. Sonnemann
    Sonnemann is the maiden surname of Emmy Göring, the German actress who became the second wife of Nazi leader Hermann Göring.
  • 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_69ca82efbce081908179b4b9c65096eb completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb850bde48190a06b77757f8c081b completed April 2, 2026, 12:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257d3fc308190b82b3731139d15cb completed April 5, 2026, 12:38 p.m.
NEDg Description generation batch_69d258b6d9c0819096dbd3e85dc6adfc completed April 5, 2026, 12:42 p.m.
NED2 Entity disambiguation (via description) batch_69d25981db3c8190b7b4935cdcc1fe1c completed April 5, 2026, 12:45 p.m.
Created at: March 30, 2026, 8:49 p.m.