Triple

T12446856
Position Surface form Disambiguated ID Type / Status
Subject Sarstedt E297421 entity
Predicate hasDistrict P459 FINISHED
Object Schulenburg E1014255 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: Schulenburg | Statement: [Sarstedt, hasDistrict, Schulenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schulenburg
Context triple: [Sarstedt, hasDistrict, Schulenburg]
  • A. Schulenburg chosen
    Schulenburg is a district-level locality within the town of Pattensen in Lower Saxony, Germany.
  • B. Siegsdorf
    Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
  • C. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • D. Judenburg
    Judenburg is a historic town in the Austrian state of Styria, known for its medieval architecture and former role as an important trading center.
  • E. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d90f18c819083a36ff4b9be4a20 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0d6947c819080d33199d331724c completed May 3, 2026, 3:28 a.m.
Created at: April 8, 2026, 9:56 p.m.