Triple

T10745963
Position Surface form Disambiguated ID Type / Status
Subject Siebengebirge region E253449 entity
Predicate contains P35 FINISHED
Object Petersberg E855158 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: Petersberg | Statement: [Siebengebirge region, contains, Petersberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Petersberg
Context triple: [Siebengebirge region, contains, Petersberg]
  • A. Petersberg
    Petersberg is a municipality in the Saalekreis district of Saxony-Anhalt, Germany, known for its rural character and proximity to the city of Halle (Saale).
  • B. Petersberg chosen
    Petersberg is a hill near Bonn in Germany best known for its historic grand hotel that has hosted numerous high-profile political events and conferences.
  • C. La Hague
    La Hague is a coastal commune in northwestern France known for its rugged cliffs, scenic landscapes, and proximity to major nuclear reprocessing facilities.
  • D. Eidsberg
    Eidsberg is a former municipality and rural town area in southeastern Norway, historically part of Østfold county and known for its agricultural landscape and cultural heritage.
  • E. Cölln
    Cölln was a historic town on the River Spree that, together with Berlin, formed the core of what later became the city of Berlin.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d711b77c4881909d16c6e82a9b86ca completed April 9, 2026, 2:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69de230b461c81909a98085079676b95 completed April 14, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:15 p.m.