Triple

T4549784
Position Surface form Disambiguated ID Type / Status
Subject Mindelheim E110132 entity
Predicate nearbyCity P350 FINISHED
Object Memmingen E301302 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: Memmingen | Statement: [Mindelheim, nearbyCity, Memmingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Memmingen
Context triple: [Mindelheim, nearbyCity, Memmingen]
  • A. Memmingen chosen
    Memmingen is a historic town in the Bavarian region of Germany, known for its well-preserved medieval old town and role as a regional transport hub.
  • B. Nucingen
    Nucingen is a powerful and unscrupulous banker in Balzac’s La Comédie humaine, emblematic of the corrupt financial elite of 19th-century Paris.
  • C. Blaubeuren
    Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
  • D. Münklingen
    Münklingen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
  • E. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • 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_69bd4412524c8190be5bcc9ddee91848 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57f3f8348190868e274ac4df87ce completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa1681708190ae4dc66e8734e5a1 completed March 21, 2026, 1:53 a.m.
Created at: March 20, 2026, 1:05 p.m.