Triple

T3389397
Position Surface form Disambiguated ID Type / Status
Subject Dieppe E71380 entity
Predicate subprefectureOf P35773 FINISHED
Object Seine-Maritime E74571 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: Seine-Maritime | Statement: [Dieppe, subprefectureOf, Seine-Maritime]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seine-Maritime
Context triple: [Dieppe, subprefectureOf, Seine-Maritime]
  • A. Seine-Maritime chosen
    Seine-Maritime is a coastal department in the Normandy region of northern France, known for its port city of Le Havre and the historic town of Rouen.
  • B. Ille-et-Vilaine
    Ille-et-Vilaine is a department in northwestern France known for its capital Rennes and its location within the historic region of Brittany.
  • C. Pas-de-Calais
    Pas-de-Calais is a department in northern France, bordering the English Channel and known for its historic ports, World War battlefields, and the Channel Tunnel connection to the United Kingdom.
  • D. Mayenne
    Mayenne is a river in western France that flows through the regions of Normandy and Pays de la Loire before joining other waterways to form the Loire basin.
  • E. Seine-et-Marne
    Seine-et-Marne is a largely rural department in north-central France east of Paris, known for its historic towns, agricultural landscapes, and attractions such as the Château de Fontainebleau and Disneyland Paris.
  • 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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb666e514819090560d43bfaf55b8 completed March 8, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b35462c69481909700f01bacdac3e1 completed March 13, 2026, 12:03 a.m.
Created at: March 8, 2026, 3:14 p.m.