Triple

T5668565
Position Surface form Disambiguated ID Type / Status
Subject Regnitz E124915 entity
Predicate hasCityOnBank P7935 FINISHED
Object 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: Bamberg | Statement: [Regnitz, hasCityOnBank, Bamberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamberg
Context triple: [Regnitz, hasCityOnBank, 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. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • D. Straubing
    Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
  • 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_69c00828906881908966f270b8f130cf completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023471f688190acec330596238a50 completed March 22, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8681d57c08190b72d1b010db3a065 completed March 28, 2026, 11:45 p.m.
Created at: March 22, 2026, 3:43 p.m.