Triple

T5181590
Position Surface form Disambiguated ID Type / Status
Subject Bamberg dialect E116932 entity
Predicate geographicCenter P1822 FINISHED
Object city of Bamberg E134924 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: city of Bamberg | Statement: [Bamberg dialect, geographicCenter, city of Bamberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Bamberg
Context triple: [Bamberg dialect, geographicCenter, city of Bamberg]
  • A. Bamberg chosen
    Bamberg is a historic city in northern Bavaria, Germany, renowned for its well-preserved medieval old town and status as a UNESCO World Heritage Site.
  • B. Coburg
    Coburg is a historic town in northern Bavaria, Germany, known for its well-preserved medieval architecture and its former role as the seat of the Duchy of Saxe-Coburg and Gotha.
  • C. Stadt Nürnberg
    Stadt Nürnberg is the municipal government of the German city of Nuremberg, responsible for local administration, public services, and urban infrastructure.
  • D. Bamberg district
    Bamberg district is a rural administrative district in the Upper Franconia region of Bavaria, Germany, surrounding but not including the city of Bamberg.
  • E. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • 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_69bd446140f08190becb93c61158f27f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd799bc58c819098a8e91e21baaef4 completed March 20, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed959004c81908e28156aae15bee6 completed March 21, 2026, 5:46 p.m.
Created at: March 20, 2026, 1:45 p.m.