Triple

T9571408
Position Surface form Disambiguated ID Type / Status
Subject Hof E230925 entity
Predicate hasMayor P185 FINISHED
Object Eva Döhla
Eva Döhla is a German local politician who serves as the mayor of the city of Hof in Bavaria.
 E821437 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: Eva Döhla | Statement: [Hof, hasMayor, Eva Döhla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Eva Döhla
Context triple: [Hof, hasMayor, Eva Döhla]
  • A. Eva Schubach
    Eva Schubach is known as a former spouse of Gerhard Schröder, the one-time Chancellor of Germany.
  • B. Verena Bentele
    Verena Bentele is a German former Paralympic biathlete and cross-country skier who became a prominent politician and disability rights advocate.
  • C. Dagmar Berghoff
    Dagmar Berghoff is a prominent German television and radio presenter best known as one of the first and most recognizable news anchors for the ARD Tagesschau.
  • D. Verena Becker
    Verena Becker is a former member of the German left-wing militant group Movement 2 June, known for her involvement in political violence and subsequent legal proceedings in the 1970s and 1980s.
  • E. Birgit Menzel
    Birgit Menzel is a scholar and academic known for her work in Slavic studies and Russian literature and culture.
  • 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: Eva Döhla
Triple: [Hof, hasMayor, Eva Döhla]
Generated description
Eva Döhla is a German local politician who serves as the mayor of the city of Hof in Bavaria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Eva Döhla
Target entity description: Eva Döhla is a German local politician who serves as the mayor of the city of Hof in Bavaria.
  • A. Eva Schubach
    Eva Schubach is known as a former spouse of Gerhard Schröder, the one-time Chancellor of Germany.
  • B. Verena Bentele
    Verena Bentele is a German former Paralympic biathlete and cross-country skier who became a prominent politician and disability rights advocate.
  • C. Dagmar Berghoff
    Dagmar Berghoff is a prominent German television and radio presenter best known as one of the first and most recognizable news anchors for the ARD Tagesschau.
  • D. Verena Becker
    Verena Becker is a former member of the German left-wing militant group Movement 2 June, known for her involvement in political violence and subsequent legal proceedings in the 1970s and 1980s.
  • E. Birgit Menzel
    Birgit Menzel is a scholar and academic known for her work in Slavic studies and Russian literature and culture.
  • 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_69ca847f22188190a56e4a97625bef22 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd998bf20881909fad48ecb16dfa31 completed April 1, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c3fa50388190bf2a1fbb50c6e0c0 completed April 5, 2026, 2:07 a.m.
NEDg Description generation batch_69d1c4eb7a0481908bbd72f6d28d4746 completed April 5, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_69d1c5c0e6e88190bbf6eb379e6d1aa3 completed April 5, 2026, 2:15 a.m.
Created at: March 30, 2026, 8:04 p.m.