Triple

T4228709
Position Surface form Disambiguated ID Type / Status
Subject König E94523 entity
Predicate hasNotableBearer P458 FINISHED
Object Michael König
Michael König is a German name shared by several notable individuals, including actors, musicians, and athletes.
 E450493 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: Michael König | Statement: [König, hasNotableBearer, Michael König]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael König
Context triple: [König, hasNotableBearer, Michael König]
  • A. Marcus König
    Marcus König is a German politician who serves as the mayor of the Bavarian city of Fürth.
  • B. Markus König
    Markus König is a relatively obscure individual whose specific public achievements or biographical details are not widely documented.
  • C. Peter König
    Peter König is a German mathematician known for his contributions to graph theory, particularly König's theorem on bipartite graphs.
  • D. Erwin König
    Erwin König is a purported German sniper officer, often considered apocryphal, who is best known from the film "Enemy at the Gates" as the elite Wehrmacht marksman dueling Soviet sniper Vasily Zaitsev at Stalingrad.
  • E. Olaf Kölzig
    Olaf Kölzig is a former German-Canadian NHL goaltender best known for his long, standout career with the Washington Capitals, including winning the Vezina Trophy in 2000.
  • 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: Michael König
Triple: [König, hasNotableBearer, Michael König]
Generated description
Michael König is a German name shared by several notable individuals, including actors, musicians, and athletes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael König
Target entity description: Michael König is a German name shared by several notable individuals, including actors, musicians, and athletes.
  • A. Marcus König
    Marcus König is a German politician who serves as the mayor of the Bavarian city of Fürth.
  • B. Markus König
    Markus König is a relatively obscure individual whose specific public achievements or biographical details are not widely documented.
  • C. Peter König
    Peter König is a German mathematician known for his contributions to graph theory, particularly König's theorem on bipartite graphs.
  • D. Erwin König
    Erwin König is a purported German sniper officer, often considered apocryphal, who is best known from the film "Enemy at the Gates" as the elite Wehrmacht marksman dueling Soviet sniper Vasily Zaitsev at Stalingrad.
  • E. Olaf Kölzig
    Olaf Kölzig is a former German-Canadian NHL goaltender best known for his long, standout career with the Washington Capitals, including winning the Vezina Trophy in 2000.
  • 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_69b3453700a08190ae88792e3dc63207 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e51817c8190bff50f2c3b5deea0 completed March 12, 2026, 11:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdacc411808190a80e0d6355c1cc60 completed March 20, 2026, 8:23 p.m.
NEDg Description generation batch_69bdb13e7d188190b17b416bb37846a3 completed March 20, 2026, 8:42 p.m.
NED2 Entity disambiguation (via description) batch_69bdb1a061448190915d0323efe5d992 completed March 20, 2026, 8:44 p.m.
Created at: March 12, 2026, 11:04 p.m.