Triple

T22588125
Position Surface form Disambiguated ID Type / Status
Subject Dresdner Bank E564855 entity
Predicate namedAfter P63 FINISHED
Object Dresden NE NERFINISHED

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: Dresden | Statement: [Dresdner Bank, namedAfter, Dresden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dresden
Context triple: [Dresdner Bank, namedAfter, Dresden]
  • A. Dresden
    Dresden is a small community within the municipality of Chatham-Kent in southwestern Ontario, Canada, known historically for its role in the Underground Railroad and Black settlement.
  • B. Dresden chosen
    Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
  • C. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • D. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • E. Magdeburg
    Magdeburg is a historic city in central Germany, known for its medieval cathedral, role as a major trading and industrial center, and location on the Elbe River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245836014819091b91ed3074742a3 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1615de7d48190b1ca46c76a1e609c completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 2:47 p.m.