Triple

T13569072
Position Surface form Disambiguated ID Type / Status
Subject Hegel's university lectures E324110 entity
Predicate editor P1954 FINISHED
Object Philipp Marheineke E356550 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: Philipp Marheineke | Statement: [Hegel's university lectures, editor, Philipp Marheineke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philipp Marheineke
Context triple: [Hegel's university lectures, editor, Philipp Marheineke]
  • A. Philipp Marheineke chosen
    Philipp Marheineke was a 19th-century German Protestant theologian associated with Hegelian thought, known for his influential work in systematic theology and church history.
  • B. Markus Häußler
    Markus Häußler is a German local politician who serves as the mayor of the town of Munderkingen in Baden-Württemberg.
  • C. Markus Häußler
    Markus Häußler is a German local politician who serves as the mayor of the municipality of Illerkirchberg in Baden-Württemberg.
  • D. Markus Vogt
    Markus Vogt is an architect known for his work on the design of the Bundesplatz in Switzerland.
  • E. Philipp Demandt
    Philipp Demandt is a German art historian and museum director known for leading major cultural institutions such as the Städel Museum and the Liebieghaus Skulpturensammlung in Frankfurt.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb00e0188819094fde44f85adb69c completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f8967288190b822ed1e115f85b2 completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:48 p.m.