Triple

T18381217
Position Surface form Disambiguated ID Type / Status
Subject Bernard II, Duke of Saxony E446448 entity
Predicate associatedWith P37 FINISHED
Object Lüneburg E74643 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: Lüneburg | Statement: [Bernard II, Duke of Saxony, associatedWith, Lüneburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lüneburg
Context triple: [Bernard II, Duke of Saxony, associatedWith, Lüneburg]
  • A. Lüneburg chosen
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • B. Northeim
    Northeim is a town in Lower Saxony, Germany, known for its medieval old town and location in the Leine River valley.
  • C. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • D. Braunschweig
    Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5179b60f88190adf39e85375bd11b completed April 19, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a05036a457481909ee7e4b1b8246797 completed May 13, 2026, 11:04 p.m.
Created at: April 10, 2026, 10:45 a.m.