Triple

T16092368
Position Surface form Disambiguated ID Type / Status
Subject Bydgoszcz E390387 entity
Predicate hasTwinTown P919 FINISHED
Object Mannheim E153078 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: Mannheim | Statement: [Bydgoszcz, hasTwinTown, Mannheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mannheim
Context triple: [Bydgoszcz, hasTwinTown, Mannheim]
  • A. Mannheim chosen
    Mannheim is a major city in southwestern Germany, known as an important industrial, commercial, and cultural center at the confluence of the Rhine and Neckar rivers.
  • B. Karlsruhe
    Karlsruhe is a major city in southwestern Germany best known as the seat of the country’s highest courts and a central hub of German constitutional jurisprudence.
  • C. Cologne
    Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
  • D. Mainz
    Mainz is a historic German city on the Rhine River known as a major ecclesiastical and political center of the Holy Roman Empire and today as the capital of the state of Rhineland-Palatinate.
  • E. Koblenz
    Koblenz is a historic German city in Rhineland-Palatinate, known for its strategic location at the confluence of the Rhine and Moselle rivers and its well-preserved fortresses and old town.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1858ed09881909bde122971d95753 completed April 17, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb7f3c9481908bdde67998263c5e completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 4:59 a.m.