Triple

T14679353
Position Surface form Disambiguated ID Type / Status
Subject Franz Gürtner E344736 entity
Predicate placeOfBirth P1 FINISHED
Object Regensburg E127596 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: Regensburg | Statement: [Franz Gürtner, placeOfBirth, Regensburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Regensburg
Context triple: [Franz Gürtner, placeOfBirth, Regensburg]
  • A. Regensburg chosen
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • B. Augsburg
    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.
  • C. Bamberg
    Bamberg is a historic city in northern Bavaria, Germany, renowned for its well-preserved medieval old town and status as a UNESCO World Heritage Site.
  • D. Kaufbeuren
    Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
  • E. 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.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb5692284819090f775be8e478522 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69febfcd67f081909f97bcf38d814a13 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 1:27 a.m.