Triple

T8720018
Position Surface form Disambiguated ID Type / Status
Subject TER Bretagne E206986 entity
Predicate connectsCity P4245 FINISHED
Object Fougères E191224 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: Fougères | Statement: [TER Bretagne, connectsCity, Fougères]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fougères
Context triple: [TER Bretagne, connectsCity, Fougères]
  • A. Fougères chosen
    Fougères is a historic town in Brittany, northwestern France, known for its impressive medieval castle and well-preserved old quarter.
  • B. Fallières
    Fallières is a French surname most notably borne by Armand Fallières, who served as President of France in the early 20th century.
  • C. Fremault
    Fremault is the surname of American film and television actress Anita Louise.
  • D. Villefontaine
    Villefontaine is a commune in the Isère department of southeastern France, known as a suburban town within the Grenoble urban area.
  • E. Langres
    Langres is a historic fortified town in northeastern France known for its well-preserved ramparts and as the birthplace of Enlightenment philosopher Denis Diderot.
  • 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_69ca835811d8819081ea00fd2a2c9a1c completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d02a52c81909f93622ae6920b80 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfeafd26f4819092f5adc1ac70148f completed April 3, 2026, 4:29 p.m.
Created at: March 30, 2026, 6:36 p.m.