Triple

T18464232
Position Surface form Disambiguated ID Type / Status
Subject Buchloe–Memmingen railway E451115 entity
Predicate endPoint P390 FINISHED
Object Memmingen NE NERFINISHED

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: [Buchloe–Memmingen railway, endPoint, Memmingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Memmingen
Context triple: [Buchloe–Memmingen railway, endPoint, 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. Menzingen
    Menzingen is a municipality in the canton of Zug in central Switzerland, known for its rural landscape and location in the pre-Alpine region.
  • C. Gechingen
    Gechingen is a small municipality in the German state of Baden-Württemberg, situated in the northern Black Forest region.
  • D. Wechingen
    Wechingen is a small rural municipality in the Bavarian region of southern Germany.
  • E. Nucingen
    Nucingen is a powerful and unscrupulous banker in Balzac’s La Comédie humaine, emblematic of the corrupt financial elite of 19th-century Paris.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e52a8190508190a74b1d3482364905 completed April 19, 2026, 7:18 p.m.
Created at: April 10, 2026, 11:33 a.m.