Triple

T2825907
Position Surface form Disambiguated ID Type / Status
Subject Saint-Germain-en-Laye E54920 entity
Predicate twinnedWith P1072 FINISHED
Object Aschaffenburg E384455 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: Aschaffenburg | Statement: [Saint-Germain-en-Laye, twinnedWith, Aschaffenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aschaffenburg
Context triple: [Saint-Germain-en-Laye, twinnedWith, Aschaffenburg]
  • A. Aschaffenburg chosen
    Aschaffenburg is a historic Bavarian city in Germany known for its riverside setting on the Main, its prominent Schloss Johannisburg castle, and its role as a regional cultural and economic center.
  • B. Backnang
    Backnang is a town in the German state of Baden-Württemberg, located northeast of Stuttgart and known for its historical center and role as a regional industrial and commuter hub.
  • C. Würzburg
    Würzburg is a historic city in southern Germany known for its baroque architecture, the Würzburg Residence palace, and its location along the Main River in the Franconia wine region.
  • D. Forchheim
    Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
  • E. Schweinfurt
    Schweinfurt is a city in northern Bavaria, Germany, historically known for its ball bearing industry and as a strategic target during World War II.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde925e688190bb390d3182f8c4f0 completed March 7, 2026, 8:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69bf06886d748190b346a1f4cc2b6f10 completed March 21, 2026, 8:58 p.m.
Created at: March 6, 2026, 9:59 p.m.