Triple

T8864498
Position Surface form Disambiguated ID Type / Status
Subject Georg Kahn-Ackermann E210979 entity
Predicate familyName P18 FINISHED
Object Kahn-Ackermann
Kahn-Ackermann is a German surname most notably borne by the politician and diplomat Georg Kahn-Ackermann.
 E762345 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: Kahn-Ackermann | Statement: [Georg Kahn-Ackermann, familyName, Kahn-Ackermann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kahn-Ackermann
Context triple: [Georg Kahn-Ackermann, familyName, Kahn-Ackermann]
  • A. Kahn
    Kahn is a surname most famously associated with Louis Kahn, the influential 20th-century architect known for his monumental and timeless modernist buildings.
  • B. Kretschmann
    Kretschmann is a German surname most prominently associated with actor Thomas Kretschmann, known for his roles in international film and television.
  • C. Eisenhauer
    Eisenhauer is a German-origin surname best known as the ancestral form of the name borne by U.S. President Dwight D. Eisenhower.
  • D. Kalmus
    Kalmus is a surname most notably associated with Herbert Kalmus, the co-founder of the pioneering color motion picture company Technicolor.
  • E. Hahn
    Hahn is a surname of German origin borne by various notable individuals across fields such as science, sports, and the arts.
  • 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: Kahn-Ackermann
Triple: [Georg Kahn-Ackermann, familyName, Kahn-Ackermann]
Generated description
Kahn-Ackermann is a German surname most notably borne by the politician and diplomat Georg Kahn-Ackermann.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kahn-Ackermann
Target entity description: Kahn-Ackermann is a German surname most notably borne by the politician and diplomat Georg Kahn-Ackermann.
  • A. Kahn
    Kahn is a surname most famously associated with Louis Kahn, the influential 20th-century architect known for his monumental and timeless modernist buildings.
  • B. Kretschmann
    Kretschmann is a German surname most prominently associated with actor Thomas Kretschmann, known for his roles in international film and television.
  • C. Eisenhauer
    Eisenhauer is a German-origin surname best known as the ancestral form of the name borne by U.S. President Dwight D. Eisenhower.
  • D. Kalmus
    Kalmus is a surname most notably associated with Herbert Kalmus, the co-founder of the pioneering color motion picture company Technicolor.
  • E. Hahn
    Hahn is a surname of German origin borne by various notable individuals across fields such as science, sports, and the arts.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610569d08190b108107dfe397f18 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0caccd88190b6464f53d0239e47 completed April 3, 2026, 11:13 a.m.
NEDg Description generation batch_69cfa1abe8248190b6db4713292bdfd3 completed April 3, 2026, 11:17 a.m.
NED2 Entity disambiguation (via description) batch_69cfa24efdc081908ef615305deb5b15 completed April 3, 2026, 11:19 a.m.
Created at: March 30, 2026, 6:51 p.m.