Triple

T6934478
Position Surface form Disambiguated ID Type / Status
Subject Elke Büdenbender E160517 entity
Predicate spouseName P13 FINISHED
Object Frank-Walter Steinmeier E31613 NE FINISHED

How this triple was built (2 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: Frank-Walter Steinmeier | Statement: [Elke Büdenbender, spouseName, Frank-Walter Steinmeier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank-Walter Steinmeier
Context triple: [Elke Büdenbender, spouseName, Frank-Walter Steinmeier]
  • A. Frank-Walter Steinmeier chosen
    Frank-Walter Steinmeier is a German politician and diplomat who has served as the President of Germany since 2017 and was previously the country’s foreign minister.
  • B. Joachim Gauck
    Joachim Gauck is a German Protestant pastor, former civil rights activist in East Germany, and the 11th President of Germany, serving from 2012 to 2017.
  • C. Olaf Scholz
    Olaf Scholz is a German politician from the Social Democratic Party (SPD) who has served as Chancellor of Germany since 2021.
  • D. Angela Merkel
    Angela Merkel is a German politician who served as Chancellor of Germany from 2005 to 2021 and became one of the most influential leaders in Europe and the world.
  • E. Una Merkel
    Una Merkel was an American stage and film actress best known for her sharp comic timing and memorable supporting roles in Hollywood films of the 1930s and 1940s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c6884e15208190b9e91487eaafcf85 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da415b1481908d70b92ecd5fd8e6 completed March 27, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76182c848819081b973683bdd235f completed March 28, 2026, 5:05 a.m.
Created at: March 27, 2026, 2:27 p.m.