Triple

T2797863
Position Surface form Disambiguated ID Type / Status
Subject Miroslav Klose E53080 entity
Predicate spouse P13 FINISHED
Object Sylwia Klose
Sylwia Klose is the wife of former German international footballer Miroslav Klose and is known for maintaining a largely private life away from the public spotlight.
E298359 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: Sylwia Klose | Statement: [Miroslav Klose, spouse, Sylwia Klose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylwia Klose
Context triple: [Miroslav Klose, spouse, Sylwia Klose]
  • A. Franziska Matzelsberger
    Franziska Matzelsberger was the second wife of Alois Hitler and the stepmother of Adolf Hitler.
  • B. Anja Tschimiakin
    Anja Tschimiakin was the first wife of Russian abstract art pioneer Wassily Kandinsky.
  • C. Maike Kohl-Richter
    Maike Kohl-Richter is a German academic and lawyer best known as the second wife and widow of former Chancellor Helmut Kohl.
  • D. Christiane Herzog
    Christiane Herzog was a German First Lady and philanthropist known for her social engagement, particularly in support of cystic fibrosis patients, during and after her husband Roman Herzog’s presidency.
  • E. Marta Kwiatkowska
    Marta Kwiatkowska is a prominent computer scientist known for her contributions to probabilistic model checking and formal verification.
  • 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: Sylwia Klose
Triple: [Miroslav Klose, spouse, Sylwia Klose]
Generated description
Sylwia Klose is the wife of former German international footballer Miroslav Klose and is known for maintaining a largely private life away from the public spotlight.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sylwia Klose
Target entity description: Sylwia Klose is the wife of former German international footballer Miroslav Klose and is known for maintaining a largely private life away from the public spotlight.
  • A. Franziska Matzelsberger
    Franziska Matzelsberger was the second wife of Alois Hitler and the stepmother of Adolf Hitler.
  • B. Anja Tschimiakin
    Anja Tschimiakin was the first wife of Russian abstract art pioneer Wassily Kandinsky.
  • C. Maike Kohl-Richter
    Maike Kohl-Richter is a German academic and lawyer best known as the second wife and widow of former Chancellor Helmut Kohl.
  • D. Christiane Herzog
    Christiane Herzog was a German First Lady and philanthropist known for her social engagement, particularly in support of cystic fibrosis patients, during and after her husband Roman Herzog’s presidency.
  • E. Marta Kwiatkowska
    Marta Kwiatkowska is a prominent computer scientist known for her contributions to probabilistic model checking and formal verification.
  • 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_69ab495a90788190941b6917e1eca3a6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abddf204148190a53f3f30d645d94c completed March 7, 2026, 8:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc66798148190bd7b163043167409 completed March 10, 2026, 7:21 a.m.
NEDg Description generation batch_69afc6e808708190a6fecd30f47d7e5a completed March 10, 2026, 7:23 a.m.
NED2 Entity disambiguation (via description) batch_69afc766c2508190af1d598eb18d38f7 completed March 10, 2026, 7:25 a.m.
Created at: March 6, 2026, 9:58 p.m.