Triple

T15502967
Position Surface form Disambiguated ID Type / Status
Subject arrondissement of Mulhouse E379006 entity
Predicate contains P35 FINISHED
Object Rixheim E454456 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: Rixheim | Statement: [arrondissement of Mulhouse, contains, Rixheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rixheim
Context triple: [arrondissement of Mulhouse, contains, Rixheim]
  • A. Rixheim chosen
    Rixheim is a commune in northeastern France’s Grand Est region, known historically for its wallpaper manufacturing industry.
  • B. Willanzheim
    Willanzheim is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian wine-growing tradition.
  • C. Marckolsheim
    Marckolsheim is a commune in northeastern France, located in the Grand Est region near the Rhine River and the German border.
  • D. Illzach
    Illzach is a commune in northeastern France’s Grand Est region, situated near the city of Mulhouse in the Haut-Rhin department.
  • E. Hombourg
    Hombourg is a village in the municipality of Plombières in the province of Liège, eastern Belgium, known for its rural landscape and historic farms.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fcc5bb88190b8a9a81419a9a38b completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6780ee3081908a0a833d887b1829 completed May 9, 2026, 4:57 p.m.
Created at: April 10, 2026, 3:54 a.m.