Triple

T15969084
Position Surface form Disambiguated ID Type / Status
Subject Minden-Ravensberg region E387272 entity
Predicate hasPart P35 FINISHED
Object Minden E177242 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: Minden | Statement: [Minden-Ravensberg region, hasPart, Minden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minden
Context triple: [Minden-Ravensberg region, hasPart, Minden]
  • A. Minden chosen
    Minden is a historic German city in North Rhine-Westphalia known for its strategic location on the Weser River and its well-preserved old town.
  • B. Minden
    Minden is a small city in northwestern Louisiana known for its historic downtown, antebellum homes, and role as the seat of Webster Parish.
  • C. Minden
    Minden is a small rural town located within the Somerset Region of Queensland, Australia.
  • D. Minde
    Minde is a civil parish in the municipality of Alcanena in central Portugal, known for its traditional culture and karst landscape.
  • E. Minden, Iowa
    Minden, Iowa is a small rural city located in western Iowa within Pottawattamie County.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1572847f08190830e30125e829766 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf1893388190800f013fab415ae7 completed May 10, 2026, 12:19 a.m.
Created at: April 10, 2026, 4:54 a.m.