Triple

T10326486
Position Surface form Disambiguated ID Type / Status
Subject Karl-Wilhelm von Schlieben E242775 entity
Predicate placeOfDeath P21 FINISHED
Object Gießen E264892 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: Gießen | Statement: [Karl-Wilhelm von Schlieben, placeOfDeath, Gießen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gießen
Context triple: [Karl-Wilhelm von Schlieben, placeOfDeath, Gießen]
  • A. Gießen chosen
    Gießen is a mid-sized university city in central Germany known for its academic institutions and role as a regional administrative and cultural center.
  • B. Kassel
    Kassel is a city in central Germany known for its cultural institutions and as the host of the renowned contemporary art exhibition documenta.
  • C. Heilbronn
    Heilbronn is a city in the German state of Baden-Württemberg known for its industrial base, wine production, and role as a regional economic and educational hub.
  • D. Wetzlar
    Wetzlar is a historic German city in the state of Hesse, known for its medieval old town and its long tradition in optics and precision engineering.
  • E. 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.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d7ce69b881909f27d97c90643634 completed April 7, 2026, 10:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69e525100e108190b4f6949695c7156e completed April 19, 2026, 6:55 p.m.
Created at: April 6, 2026, 11:51 a.m.