Triple

T4366086
Position Surface form Disambiguated ID Type / Status
Subject Stadtholder of Lingen E98775 entity
Predicate appliesToJurisdiction P82 FINISHED
Object Lingen E217689 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: Lingen | Statement: [Stadtholder of Lingen, appliesToJurisdiction, Lingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lingen
Context triple: [Stadtholder of Lingen, appliesToJurisdiction, Lingen]
  • A. Lingen chosen
    Lingen is a town in Lower Saxony, Germany, known for its location on the River Ems and its role as a regional economic and cultural center.
  • B. Aurich
    Aurich is a historic town in northwestern Germany that serves as one of the principal urban centers of the East Frisia region in Lower Saxony.
  • C. Wallhausen
    Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
  • D. Lauenburg
    Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
  • E. Heringsdorf
    Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35200263081909bb326a4d7a8db99 completed March 12, 2026, 11:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbcbbd1881908eb9f0ea6b2fe16b completed March 14, 2026, 10:06 p.m.
Created at: March 12, 2026, 11:17 p.m.