Triple

T4228708
Position Surface form Disambiguated ID Type / Status
Subject König E94523 entity
Predicate hasNotableBearer P458 FINISHED
Object Markus König
Markus König is a relatively obscure individual whose specific public achievements or biographical details are not widely documented.
E449420 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: Markus König | Statement: [König, hasNotableBearer, Markus König]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Markus König
Context triple: [König, hasNotableBearer, Markus König]
  • A. Christoph Dolle
    Christoph Dolle is a German local politician who serves as the mayor of the town of Blomberg.
  • B. Andreas Hügerich
    Andreas Hügerich is a German local politician who serves as the mayor of the town of Lichtenfels in Bavaria.
  • C. Peter König
    Peter König is a German mathematician known for his contributions to graph theory, particularly König's theorem on bipartite graphs.
  • D. 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.
  • E. Johannes Popitz
    Johannes Popitz was a German lawyer, conservative politician, and high-ranking finance official who served as Prussian finance minister and later became involved in resistance circles against the Nazi regime.
  • 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: Markus König
Triple: [König, hasNotableBearer, Markus König]
Generated description
Markus König is a relatively obscure individual whose specific public achievements or biographical details are not widely documented.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Markus König
Target entity description: Markus König is a relatively obscure individual whose specific public achievements or biographical details are not widely documented.
  • A. Christoph Dolle
    Christoph Dolle is a German local politician who serves as the mayor of the town of Blomberg.
  • B. Andreas Hügerich
    Andreas Hügerich is a German local politician who serves as the mayor of the town of Lichtenfels in Bavaria.
  • C. Peter König
    Peter König is a German mathematician known for his contributions to graph theory, particularly König's theorem on bipartite graphs.
  • D. 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.
  • E. Johannes Popitz
    Johannes Popitz was a German lawyer, conservative politician, and high-ranking finance official who served as Prussian finance minister and later became involved in resistance circles against the Nazi regime.
  • 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_69bda4073aa88190ba64691b93aab900 completed March 20, 2026, 7:46 p.m.
NEDg Description generation batch_69bda586202c8190960d36bdaa1284a7 completed March 20, 2026, 7:52 p.m.
NED2 Entity disambiguation (via description) batch_69bda5dd44388190861ddf5f689b739c completed March 20, 2026, 7:54 p.m.
Created at: March 12, 2026, 11:04 p.m.