Triple

T7531553
Position Surface form Disambiguated ID Type / Status
Subject 2014 Russian Grand Prix E178033 entity
Predicate circuitDesigner P30561 FINISHED
Object Hermann Tilke E188554 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: Hermann Tilke | Statement: [2014 Russian Grand Prix, circuitDesigner, Hermann Tilke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hermann Tilke
Context triple: [2014 Russian Grand Prix, circuitDesigner, Hermann Tilke]
  • A. Hermann Tilke chosen
    Hermann Tilke is a German engineer and circuit designer best known for creating many modern Formula One racetracks around the world.
  • B. Uwe Schlaich
    Uwe Schlaich is a German architect known for designing the main building of the Topography of Terror documentation center in Berlin.
  • C. Andreas Schlüter
    Andreas Schlüter was a prominent German Baroque sculptor and architect best known for his influential work in Prussia at the turn of the 18th century.
  • D. Andreas Schlüter
    Andreas Schlüter is a German local politician who serves as the mayor of the municipality of Gerswalde in Brandenburg.
  • E. Frank Kracht
    Frank Kracht is a German local politician who serves as the mayor of the Baltic Sea town of Sassnitz.
  • 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_69c69f2acdbc8190b5a8320168c1d0ba completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8217b1c8190b3db453cee0fc4fd completed March 27, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8463e08ac8190abd4d19b58067233 completed March 28, 2026, 9:21 p.m.
Created at: March 27, 2026, 3:47 p.m.