Triple

T13605165
Position Surface form Disambiguated ID Type / Status
Subject Gare de Besançon-Viotte E325041 entity
Predicate connectsTo P845 FINISHED
Object Mulhouse E78039 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: Mulhouse | Statement: [Gare de Besançon-Viotte, connectsTo, Mulhouse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mulhouse
Context triple: [Gare de Besançon-Viotte, connectsTo, Mulhouse]
  • A. Mulhouse chosen
    Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
  • B. Strasbourg
    Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
  • C. Illkirch-Graffenstaden
    Illkirch-Graffenstaden is a suburban commune in northeastern France, located just south of Strasbourg in the Grand Est region.
  • D. Altkirch
    Altkirch is a small historic town in northeastern France that serves as an administrative and cultural center in the Alsace region.
  • E. Besançon
    Besançon is a historic city in eastern France, known for its well-preserved Vauban fortifications, rich cultural heritage, and role as a regional administrative and educational 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb07e442c819086a8cbb967c03ad3 completed April 12, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8c6cde08190b79fdcde8a81ccc4 completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 9:50 p.m.