Triple

T8733248
Position Surface form Disambiguated ID Type / Status
Subject Teutoburg Forest E207308 entity
Predicate near P350 FINISHED
Object city of Osnabrück E22113 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 Osnabrück | Statement: [Teutoburg Forest, near, city of Osnabrück]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Osnabrück
Context triple: [Teutoburg Forest, near, city of Osnabrück]
  • A. Osnabrück chosen
    Osnabrück is a historic city in Lower Saxony, Germany, known for its medieval architecture and role in the Peace of Westphalia.
  • B. Münster
    Münster is a historic city in western Germany known as one of the principal sites where the Peace of Westphalia treaties were negotiated and signed, ending the Thirty Years' War in 1648.
  • C. Hildesheim
    Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
  • D. Township of Osnabruck
    The Township of Osnabruck was a former municipality in eastern Ontario, Canada, that later became part of the Township of South Stormont through amalgamation.
  • E. Stadthagen
    Stadthagen is a historic town in Lower Saxony, Germany, known for its Renaissance architecture and role as an administrative and cultural center of the surrounding region.
  • 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_69ca8358e4008190898471a59b96c301 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d2903b08190a5ef29b6d6ca5f1c completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf292d71ec819082095cb7b8b2d39c completed April 3, 2026, 2:42 a.m.
Created at: March 30, 2026, 6:37 p.m.