Triple

T5047492
Position Surface form Disambiguated ID Type / Status
Subject Margaret of Schleswig-Holstein-Sonderburg E113701 entity
Predicate associatedWith P37 FINISHED
Object Nassau-Siegen E457423 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: Nassau-Siegen | Statement: [Margaret of Schleswig-Holstein-Sonderburg, associatedWith, Nassau-Siegen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nassau-Siegen
Context triple: [Margaret of Schleswig-Holstein-Sonderburg, associatedWith, Nassau-Siegen]
  • A. Nassau-Siegen chosen
    Nassau-Siegen was a German county in the Holy Roman Empire centered on the town of Siegen and ruled by a branch of the House of Nassau.
  • B. Nassau-Weilburg
    Nassau-Weilburg was a historical German county and later principality within the Holy Roman Empire, ruled by a branch of the House of Nassau.
  • C. Badenburg
    Badenburg is an ornate pavilion within Munich’s Nymphenburg Palace park, known for its richly decorated interiors and historical bathing hall.
  • D. Stolberg
    Stolberg is a historic German town in the Harz region, known for its well-preserved medieval architecture and role in early Reformation-era history.
  • E. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd740002b48190bc7aa176d734c589 completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea47e5ba0819088217a9ad3ce2b0a completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:37 p.m.