Triple

T14347763
Position Surface form Disambiguated ID Type / Status
Subject Eurométropole de Strasbourg E355770 entity
Predicate contains P35 FINISHED
Object Oberhausbergen E1104977 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: Oberhausbergen | Statement: [Eurométropole de Strasbourg, contains, Oberhausbergen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oberhausbergen
Context triple: [Eurométropole de Strasbourg, contains, Oberhausbergen]
  • A. Niederhausbergen chosen
    Niederhausbergen is a small commune in northeastern France, situated near the city of Strasbourg in the Grand Est region.
  • B. Beutelsbach
    Beutelsbach is a small municipality in the rural Passau district of Lower Bavaria in southeastern Germany.
  • C. Meinisberg
    Meinisberg is a small municipality in the canton of Bern in Switzerland, situated near the city of Biel/Bienne.
  • D. Odelzhausen
    Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
  • E. Obergoms
    Obergoms is a municipality in the canton of Valais in southwestern Switzerland, known for its high Alpine landscapes and traditional mountain villages.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e8d081c8190ac805726a3e98f4c completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe249ebd3c81908d8b562845d9ceb1 completed May 8, 2026, 5:59 p.m.
Created at: April 10, 2026, 1:14 a.m.