Triple

T4778670
Position Surface form Disambiguated ID Type / Status
Subject Worms, Germany E106116 entity
Predicate twinTown P1072 FINISHED
Object Auxerre, France E19328 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: Auxerre, France | Statement: [Worms, Germany, twinTown, Auxerre, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Auxerre, France
Context triple: [Worms, Germany, twinTown, Auxerre, France]
  • A. Auxerre, France chosen
    Auxerre, France is a historic city in the Burgundy region known for its medieval architecture, Gothic cathedral, and role as a cultural and economic center along the Yonne River.
  • B. Fourchambault, France
    Fourchambault, France is a small industrial town in the Nièvre department of central France, historically known for its steelworks and metallurgical industry.
  • C. Bourges, France
    Bourges, France is a historic city in central France known for its well-preserved medieval architecture and the UNESCO-listed Bourges Cathedral.
  • D. Gouvieux, France
    Gouvieux, France is a commune in the Oise department in northern France, known for its affluent residential character and association with the Aga Khan IV.
  • E. Douai, France
    Douai, France is a historic town in northern France known for its medieval belfry, legal and university traditions, and role as a regional administrative 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_69bd43f3074c8190937e7b0a457fe9f1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd658942e481908570cfec77fe4a4b completed March 20, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69be43cecc748190a410c262aa2e4b98 completed March 21, 2026, 7:07 a.m.
Created at: March 20, 2026, 1:21 p.m.