Triple

T14391810
Position Surface form Disambiguated ID Type / Status
Subject Rupert, King of Germany E356860 entity
Predicate birthPlace P1 FINISHED
Object Amberg E267893 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: Amberg | Statement: [Rupert, King of Germany, birthPlace, Amberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amberg
Context triple: [Rupert, King of Germany, birthPlace, Amberg]
  • A. Amberg chosen
    Amberg is a historic town in Bavaria, Germany, known for its well-preserved medieval old town and former role as a regional administrative and trading center.
  • B. Amberg-Sulzbach
    Amberg-Sulzbach is a rural district in the Bavarian region of Upper Palatinate in Germany, known for its mix of historic towns, forests, and former mining areas.
  • C. Deggendorf
    Deggendorf is a town in southeastern Germany situated on the Danube River, known as a regional commercial and transportation hub near the Bavarian Forest.
  • D. Straubing
    Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
  • E. Zwiesel
    Zwiesel is a prominent mountain in the Bavarian Alps of southeastern Germany, known for its scenic hiking routes and panoramic views over the Bad Reichenhall area.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de902b9acc8190817ffa848a76a880 completed April 14, 2026, 7:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00179824c88190aeef28a08eb1a0c9 completed May 10, 2026, 5:28 a.m.
Created at: April 10, 2026, 1:16 a.m.