Triple

T2024152
Position Surface form Disambiguated ID Type / Status
Subject David Einhorn E44168 entity
Predicate residence P75 FINISHED
Object Munich, Bavaria E21335 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: Munich, Bavaria | Statement: [David Einhorn, residence, Munich, Bavaria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munich, Bavaria
Context triple: [David Einhorn, residence, Munich, Bavaria]
  • A. Munich chosen
    Munich is the capital and largest city of the German state of Bavaria, renowned for its rich cultural scene, historic architecture, and the annual Oktoberfest beer festival.
  • B. Ingolstadt
    Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
  • C. Munich metropolitan region
    The Munich metropolitan region is a major economic and cultural hub in southern Germany centered around the city of Munich and encompassing numerous surrounding towns and districts.
  • D. Leverkusen
    Leverkusen is a city in western Germany, known for its chemical industry and as the home of the football club Bayer 04 Leverkusen.
  • E. Würzburg, Germany
    Würzburg, Germany is a historic city in northern Bavaria known for its baroque and rococo architecture, prominent university, and renowned Franconian wine culture.
  • 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_69a8891201bc8190aca837be6de41579 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb8f2cd5c8190b19da6f6aa2001d6 completed March 7, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe86f11108190a1987c1cee133d56 completed March 10, 2026, 9:46 a.m.
Created at: March 4, 2026, 7:38 p.m.