Triple

T5953068
Position Surface form Disambiguated ID Type / Status
Subject Schaumburg, Lower Saxony, Germany E132443 entity
Predicate locatedNear P294 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: [Schaumburg, Lower Saxony, Germany, locatedNear, Minden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minden
Context triple: [Schaumburg, Lower Saxony, Germany, locatedNear, 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, Iowa
    Minden, Iowa is a small rural city located in western Iowa within Pottawattamie County.
  • C. Minden, Nevada
    Minden, Nevada is a small unincorporated town in western Nevada known as a historic community in the Carson Valley near the Sierra Nevada.
  • D. Meridian
    Meridian is a rapidly growing suburban city in southwestern Idaho, known for its family-friendly neighborhoods and proximity to Boise.
  • E. Meridian
    Meridian is a 1976 novel by Alice Walker that explores the civil rights movement through the life of a young Black woman activist in the American South.
  • 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_69c0086b05cc8190a8f36a96927a525c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03983b8848190afaa37f35c95bad6 completed March 22, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3d1801c819093dc43dc5a525796 completed March 23, 2026, 6:55 a.m.
Created at: March 22, 2026, 4:02 p.m.