Triple

T15749843
Position Surface form Disambiguated ID Type / Status
Subject Emilie Schindler E381817 entity
Predicate placeOfDeath P21 FINISHED
Object Strausberg E662465 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: Strausberg | Statement: [Emilie Schindler, placeOfDeath, Strausberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Strausberg
Context triple: [Emilie Schindler, placeOfDeath, Strausberg]
  • A. Strausberg chosen
    Strausberg is a town in Brandenburg, Germany, historically notable as a military center and former base of the East German Air Force.
  • B. Luckenwalde
    Luckenwalde is a town in the German state of Brandenburg known for its industrial heritage and historic architecture, including notable factory complexes.
  • C. Rheinsberg
    Rheinsberg is a small historic town in Brandenburg, Germany, best known for its picturesque lakeside palace that served as a residence for Prussian royalty.
  • D. Zossen
    Zossen is a town in Brandenburg, Germany, historically notable as a major military command center, including serving as a key headquarters area during the Soviet occupation after World War II.
  • E. Teterow
    Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0502fd3608190b42e647b9c2b41a1 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0035450810819092796c556dfa8ed3 completed May 10, 2026, 7:35 a.m.
Created at: April 10, 2026, 4:46 a.m.