Triple

T2256703
Position Surface form Disambiguated ID Type / Status
Subject Haut-Rhin E49743 entity
Predicate contains P35 FINISHED
Object Saint-Louis E91160 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: Saint-Louis | Statement: [Haut-Rhin, contains, Saint-Louis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint-Louis
Context triple: [Haut-Rhin, contains, Saint-Louis]
  • A. Saint-Louis chosen
    Saint-Louis is a French border town in the Alsace region, adjacent to Basel and known as a key cross-border transit and commuter hub between France, Switzerland, and Germany.
  • B. Saint-Louis
    Saint-Louis is a historic coastal city in northwestern Senegal that served as a major colonial administrative and trading center in French West Africa.
  • C. Orléans
    Orléans is a federal electoral district in the eastern part of Ottawa, Ontario, represented in the House of Commons of Canada.
  • D. Orléans
    Orléans is a historic city in north-central France, renowned for its association with Joan of Arc and its location on the Loire River.
  • E. Orleans
    Orleans is a coastal town on outer Cape Cod in Massachusetts known for its beaches, fishing, and role as a popular summer vacation destination.
  • 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_69a88aaa9250819095e127d0d77e8a32 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc1570dc88190bb2b17ed4c25dbb5 completed March 7, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71c69f088190a38254a8a3670124 completed March 9, 2026, 7:07 a.m.
Created at: March 4, 2026, 7:47 p.m.