Triple

T12877868
Position Surface form Disambiguated ID Type / Status
Subject Leipzig metropolitan region E308012 entity
Predicate containsCity P294 FINISHED
Object Belgershain E842727 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: Belgershain | Statement: [Leipzig metropolitan region, containsCity, Belgershain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belgershain
Context triple: [Leipzig metropolitan region, containsCity, Belgershain]
  • A. Belgershain chosen
    Belgershain is a small municipality in the Leipzig district of Saxony, Germany, situated southeast of the city of Leipzig.
  • B. Breyten
    Breyten is the given name of Breyten Breytenbach, the renowned South African poet, painter, and anti-apartheid activist.
  • C. Bechtsrieth
    Bechtsrieth is a small municipality in the Upper Palatinate region of Bavaria, Germany.
  • D. Wassenberg
    Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
  • E. Stutterheim
    Stutterheim is a small town in South Africa’s Eastern Cape province, known for its forestry, agriculture, and scenic setting near the Amathole Mountains.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af55623081909fd171129f439302 completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:38 p.m.