Triple

T4658144
Position Surface form Disambiguated ID Type / Status
Subject John VII, Count of Nassau-Siegen E102458 entity
Predicate hasTerritorialBase P21614 FINISHED
Object Siegen E289225 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: Siegen | Statement: [John VII, Count of Nassau-Siegen, hasTerritorialBase, Siegen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siegen
Context triple: [John VII, Count of Nassau-Siegen, hasTerritorialBase, Siegen]
  • A. Siegen chosen
    Siegen is a city in western Germany known as the birthplace of the Baroque painter Peter Paul Rubens and for its historic mining and university traditions.
  • B. Siegen-Wittgenstein
    Siegen-Wittgenstein is a rural district in the German state of North Rhine-Westphalia, known for its forested low mountain landscapes and the city of Siegen as its administrative center.
  • C. Heppenheim
    Heppenheim is a historic town in southwestern Germany, known for its picturesque old town, vineyards, and location on the Bergstraße at the edge of the Odenwald.
  • D. Wuppertal
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • E. Kaiserslautern
    Kaiserslautern is a city in southwestern Germany known for its historic old town, technical university, and prominent football club 1. FC Kaiserslautern.
  • 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63271a548190bd9662b69a45d9a5 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cad46d4081908f685d961d100d42 completed March 27, 2026, 6:22 p.m.
Created at: March 20, 2026, 1:15 p.m.