Triple

T8789852
Position Surface form Disambiguated ID Type / Status
Subject Inning am Ammersee E209134 entity
Predicate hasMayor P185 FINISHED
Object Michaela Reichelt
Michaela Reichelt is a German local politician who serves as the mayor of the municipality of Inning am Ammersee in Bavaria.
E769945 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: Michaela Reichelt | Statement: [Inning am Ammersee, hasMayor, Michaela Reichelt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michaela Reichelt
Context triple: [Inning am Ammersee, hasMayor, Michaela Reichelt]
  • A. Michaela Dorfmeister
    Michaela Dorfmeister is a retired Austrian alpine ski racer renowned for winning multiple World Cup titles and Olympic gold medals in the early 2000s.
  • B. Verena Rehm
    Verena Rehm is a German singer and songwriter best known as the female vocalist for the Eurodance project Groove Coverage.
  • C. Anja Lechner
    Anja Lechner is a German cellist renowned for her versatile performances spanning classical, contemporary, and world music collaborations.
  • D. Anja Tschimiakin
    Anja Tschimiakin was the first wife of Russian abstract art pioneer Wassily Kandinsky.
  • E. Julia Jentsch
    Julia Jentsch is a German actress acclaimed for her powerful performances in films such as "Sophie Scholl – The Final Days" and numerous other European cinema and television productions.
  • 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: Michaela Reichelt
Triple: [Inning am Ammersee, hasMayor, Michaela Reichelt]
Generated description
Michaela Reichelt is a German local politician who serves as the mayor of the municipality of Inning am Ammersee in Bavaria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michaela Reichelt
Target entity description: Michaela Reichelt is a German local politician who serves as the mayor of the municipality of Inning am Ammersee in Bavaria.
  • A. Michaela Dorfmeister
    Michaela Dorfmeister is a retired Austrian alpine ski racer renowned for winning multiple World Cup titles and Olympic gold medals in the early 2000s.
  • B. Verena Rehm
    Verena Rehm is a German singer and songwriter best known as the female vocalist for the Eurodance project Groove Coverage.
  • C. Anja Lechner
    Anja Lechner is a German cellist renowned for her versatile performances spanning classical, contemporary, and world music collaborations.
  • D. Anja Tschimiakin
    Anja Tschimiakin was the first wife of Russian abstract art pioneer Wassily Kandinsky.
  • E. Julia Jentsch
    Julia Jentsch is a German actress acclaimed for her powerful performances in films such as "Sophie Scholl – The Final Days" and numerous other European cinema and television productions.
  • 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_69ca836168108190bb43d3dc235c1f55 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f8d25f881908863d636fa57a8a2 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfc921d3408190a2f823473bf9b4bc completed April 3, 2026, 2:05 p.m.
NEDg Description generation batch_69cfcccaea508190ac9c0b2d2b496c5c completed April 3, 2026, 2:20 p.m.
NED2 Entity disambiguation (via description) batch_69cfcd1dd12881909d250c08feeb9fbf completed April 3, 2026, 2:22 p.m.
Created at: March 30, 2026, 6:43 p.m.