Triple

T12105085
Position Surface form Disambiguated ID Type / Status
Subject Schwartz E288281 entity
Predicate hasVariant P455 FINISHED
Object Schwarz E803074 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: Schwarz | Statement: [Schwartz, hasVariant, Schwarz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwarz
Context triple: [Schwartz, hasVariant, Schwarz]
  • A. Schwarz
    Schwarz is a theoretical physicist best known as one of the pioneers of string theory and for his work on anomaly cancellation.
  • B. Schwarz chosen
    Schwarz is a common German surname borne by numerous notable individuals across fields such as science, politics, and the arts.
  • C. Schwaz
    Schwaz is a historic silver-mining town in the Austrian state of Tyrol, known for its medieval center and alpine setting.
  • D. Blau
    The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
  • E. Schwarzhuber
    Schwarzhuber is a German surname most notably associated with Johann Schwarzhuber, an SS officer and concentration camp official during World War II.
  • 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_69d6ab4a5c448190a110d1273314b21a completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d91561eaec819096ba00682d81f41a completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f677039481908f14fa12b9b86910 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.