Triple

T2637060
Position Surface form Disambiguated ID Type / Status
Subject Evesham E59769 entity
Predicate twinnedWith P1072 FINISHED
Object Molsheim, France E165223 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: Molsheim, France | Statement: [Evesham, twinnedWith, Molsheim, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Molsheim, France
Context triple: [Evesham, twinnedWith, Molsheim, France]
  • A. Molsheim chosen
    Molsheim is a historic town in northeastern France’s Grand Est region, known for its medieval architecture and as the birthplace of the Bugatti automobile brand.
  • B. Mondorf-les-Bains
    Mondorf-les-Bains is a spa town in southeastern Luxembourg renowned for its thermal baths, wellness facilities, and casino.
  • C. Mulhouse
    Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
  • D. Schiltigheim
    Schiltigheim is a suburban commune in northeastern France, located just north of Strasbourg and known historically for its brewing industry.
  • E. Haguenau
    Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local economic center.
  • 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8e3190081908ea828fe79569cc9 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90b3e9b48190857ae21022a4fb15 completed March 10, 2026, 3:32 a.m.
Created at: March 6, 2026, 9:50 p.m.