Triple

T14009784
Position Surface form Disambiguated ID Type / Status
Subject The Student Prince E337047 entity
Predicate setting P1957 FINISHED
Object Heidelberg E15415 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: Heidelberg | Statement: [The Student Prince, setting, Heidelberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heidelberg
Context triple: [The Student Prince, setting, Heidelberg]
  • A. Heidelberg
    Heidelberg is a suburb of Melbourne, Australia, known for its historic role in Australian Impressionism and its location along the Yarra River.
  • B. Heidelberg
    Heidelberg is a South African town known for its historical significance and role as a regional service and commercial center.
  • C. Heidelberg chosen
    Heidelberg is a historic university city in southwestern Germany renowned for its picturesque old town, castle ruins, and one of Europe’s oldest universities.
  • D. Heidberg
    Heidberg is a small locality or district that forms part of the town of Rüthen in North Rhine-Westphalia, Germany.
  • E. Karlsruhe
    Karlsruhe is a major city in southwestern Germany best known as the seat of the country’s highest courts and a central hub of German constitutional jurisprudence.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed44f90819099ad08c09c066b56 completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd27f0e59c8190b40213e999c75feb completed May 8, 2026, 12:01 a.m.
Created at: April 9, 2026, 10:19 p.m.