Triple

T10079531
Position Surface form Disambiguated ID Type / Status
Subject Hennigsdorf E213861 entity
Predicate borderedBy P224 FINISHED
Object Velten E380237 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: Velten | Statement: [Hennigsdorf, borderedBy, Velten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Velten
Context triple: [Hennigsdorf, borderedBy, Velten]
  • A. Velten chosen
    Velten is a small town in the German state of Brandenburg, known historically for its stove and ceramics industry and its location just northwest of Berlin.
  • B. Lennestadt
    Lennestadt is a town in the Olpe district of North Rhine-Westphalia, Germany, known for its location in the hilly, forested Sauerland region and its mix of industry and tourism.
  • C. Brannenburg
    Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
  • D. Kostheim
    Kostheim is a district of the city of Wiesbaden in the German state of Hesse, located on the right bank of the Rhine opposite Mainz.
  • E. Thiensville
    Thiensville is a small village in southeastern Wisconsin, known as a suburban community within the Milwaukee metropolitan 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd031ce748190bb71189afd331979 completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29ad406d88190a72c5a62b3586f47 completed April 5, 2026, 5:24 p.m.
Created at: March 30, 2026, 9 p.m.