Triple

T1527649
Position Surface form Disambiguated ID Type / Status
Subject Auguste Piccard E32370 entity
Predicate placeOfEvent P373 FINISHED
Object Augsburg E127006 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: Augsburg | Statement: [Auguste Piccard, placeOfEvent, Augsburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Augsburg
Context triple: [Auguste Piccard, placeOfEvent, Augsburg]
  • A. Augsburg chosen
    Augsburg is one of Germany’s oldest cities, a historic Bavarian center known for its rich Renaissance heritage and role as a major medieval trading hub.
  • B. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • C. Landshut
    Landshut is a historic Bavarian city in southeastern Germany known for its well-preserved medieval architecture and the landmark Trausnitz Castle.
  • D. Ulm
    Ulm is a historic city in the German state of Baden-Württemberg, best known for its towering Gothic cathedral and as the birthplace of physicist Albert Einstein.
  • E. Würzburg
    Würzburg is a historic city in southern Germany known for its baroque architecture, the Würzburg Residence palace, and its location along the Main River in the Franconia wine region.
  • 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_69a885e9b0ac819093a9806ad0efc82c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90812cb1c819099e7ad48fedcbe94 completed March 5, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69b261a163a08190bd5bdb95725e4072 completed March 12, 2026, 6:48 a.m.
Created at: March 4, 2026, 7:26 p.m.