Triple

T22429493
Position Surface form Disambiguated ID Type / Status
Subject Mulhouse–Thann railway E554459 entity
Predicate locatedIn P40 FINISHED
Object Haut-Rhin 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: Haut-Rhin | Statement: [Mulhouse–Thann railway, locatedIn, Haut-Rhin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haut-Rhin
Context triple: [Mulhouse–Thann railway, locatedIn, Haut-Rhin]
  • A. Haut-Rhin chosen
    Haut-Rhin is a department in the Grand Est region of northeastern France, bordering Germany and Switzerland and known for its Alsatian culture and wine-producing villages.
  • B. Bas-Rhin
    Bas-Rhin is a department in the Grand Est region of northeastern France, known for its border with Germany and its capital, the European institutional city of Strasbourg.
  • C. Meurthe-et-Moselle
    Meurthe-et-Moselle is a department in northeastern France known for its capital Nancy, rich industrial history, and Art Nouveau architectural heritage.
  • D. Sundgau
    Sundgau is a rural, hilly region in southern Alsace, France, known for its traditional villages, forests, and distinctive Alsatian culture.
  • E. Pays de Bitche
    Pays de Bitche is a rural, hilly region in northeastern France’s Moselle department, known for its fortified towns, forests, and location within the Northern Vosges.
  • 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_69e11e4f2d0c819091aa3558ea2ee630 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15a30109481908724a0cf7596d105 completed April 29, 2026, 1:09 a.m.
Created at: April 16, 2026, 8:47 p.m.