Triple

T15955827
Position Surface form Disambiguated ID Type / Status
Subject Salzlandkreis E386930 entity
Predicate containsTown P847 FINISHED
Object Staßfurt E597687 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: Staßfurt | Statement: [Salzlandkreis, containsTown, Staßfurt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Staßfurt
Context triple: [Salzlandkreis, containsTown, Staßfurt]
  • A. Staßfurt chosen
    Staßfurt is a town in Saxony-Anhalt, Germany, historically known for its salt mining and chemical industry.
  • B. Querfurt
    Querfurt is a small historic town in the German state of Saxony-Anhalt, known for its well-preserved medieval castle and old town.
  • C. Fritzlar
    Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
  • D. Filderstadt
    Filderstadt is a town in the German state of Baden-Württemberg, situated just south of Stuttgart and known for its proximity to Stuttgart Airport and role as a regional transport hub.
  • E. Suhl
    Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
  • 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156fb29848190a55cabb49cb19575 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139e380bc81908452f6e8666f23ad completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 4:53 a.m.