Triple

T19938406
Position Surface form Disambiguated ID Type / Status
Subject Heidelberg (Gauteng) E479236 entity
Predicate namedAfter P63 FINISHED
Object Heidelberg (Germany) NE NERFINISHED

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 (Germany) | Statement: [Heidelberg (Gauteng), namedAfter, Heidelberg (Germany)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heidelberg (Germany)
Context triple: [Heidelberg (Gauteng), namedAfter, Heidelberg (Germany)]
  • A. 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.
  • B. Heidelberg
    Heidelberg is a suburb of Melbourne, Australia, known for its historic role in Australian Impressionism and its location along the Yarra River.
  • C. Heidelberg
    Heidelberg is a South African town known for its historical significance and role as a regional service and commercial center.
  • D. Heidberg
    Heidberg is a small locality or district that forms part of the town of Rüthen in North Rhine-Westphalia, Germany.
  • E. Tübingen, Germany
    Tübingen, Germany, is a historic university town in the state of Baden-Württemberg known for its medieval old town and renowned Eberhard Karls University.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e522a17c819095165d4d24939fd8 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a190ac08190b9dc7955c9764a71 completed April 20, 2026, 4:53 p.m.
Created at: April 10, 2026, 1:53 p.m.