Triple

T15610904
Position Surface form Disambiguated ID Type / Status
Subject Eschweiler E375285 entity
Predicate hasMayor P185 FINISHED
Object Nadja Zikes
Nadja Zikes is a German local politician who serves as the mayor of the city of Eschweiler in North Rhine-Westphalia.
E1167025 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: Nadja Zikes | Statement: [Eschweiler, hasMayor, Nadja Zikes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nadja Zikes
Context triple: [Eschweiler, hasMayor, Nadja Zikes]
  • A. Nadja Schildknecht
    Nadja Schildknecht is a Swiss film producer and cultural entrepreneur best known as a co-founder and driving force behind the internationally recognized Zurich Film Festival.
  • B. Nicole Kruspe
    Nicole Kruspe is a linguist known for her extensive research and documentation of Aslian languages spoken by indigenous communities in the Malay Peninsula.
  • C. Nina Eichinger
    Nina Eichinger is a German television presenter and actress known for her work on various entertainment and music programs.
  • D. Nadia Landowski
    Nadia Landowski was a French sculptor and painter, known as the daughter of renowned sculptor Paul Landowski and for her own contributions to 20th-century French art.
  • E. Nina Varzar
    Nina Varzar was the wife of renowned Soviet composer Dmitri Shostakovich and a physicist by profession.
  • 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: Nadja Zikes
Triple: [Eschweiler, hasMayor, Nadja Zikes]
Generated description
Nadja Zikes is a German local politician who serves as the mayor of the city of Eschweiler in North Rhine-Westphalia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nadja Zikes
Target entity description: Nadja Zikes is a German local politician who serves as the mayor of the city of Eschweiler in North Rhine-Westphalia.
  • A. Nadja Schildknecht
    Nadja Schildknecht is a Swiss film producer and cultural entrepreneur best known as a co-founder and driving force behind the internationally recognized Zurich Film Festival.
  • B. Nicole Kruspe
    Nicole Kruspe is a linguist known for her extensive research and documentation of Aslian languages spoken by indigenous communities in the Malay Peninsula.
  • C. Nina Eichinger
    Nina Eichinger is a German television presenter and actress known for her work on various entertainment and music programs.
  • D. Nadia Landowski
    Nadia Landowski was a French sculptor and painter, known as the daughter of renowned sculptor Paul Landowski and for her own contributions to 20th-century French art.
  • E. Nina Varzar
    Nina Varzar was the wife of renowned Soviet composer Dmitri Shostakovich and a physicist by profession.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e8024948190a6c711f2e5c2aac4 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56d76c108190aa3cae2d7e17c301 completed May 9, 2026, 3:46 p.m.
NEDg Description generation batch_69ff57c304188190afa695ae88cf0234 completed May 9, 2026, 3:50 p.m.
NED2 Entity disambiguation (via description) batch_69ff5920436c81909addad5bb4566ae9 completed May 9, 2026, 3:56 p.m.
Created at: April 10, 2026, 4:13 a.m.