Triple

T8774030
Position Surface form Disambiguated ID Type / Status
Subject French A8 motorway E208532 entity
Predicate passesNear P416 FINISHED
Object Fréjus E214446 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: Fréjus | Statement: [French A8 motorway, passesNear, Fréjus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fréjus
Context triple: [French A8 motorway, passesNear, Fréjus]
  • A. Fréjus chosen
    Fréjus is a historic town and seaside resort on the French Riviera in southeastern France, known for its Roman ruins and Mediterranean coastline.
  • B. Port de Saint-Raphaël
    Port de Saint-Raphaël is a Mediterranean marina and harbor in the coastal town of Saint-Raphaël on the French Riviera, serving both leisure boating and local maritime activities.
  • C. Hyères
    Hyères is a coastal town in southeastern France known for its Mediterranean climate, historic old town, and nearby Golden Islands (Îles d’Hyères).
  • D. La Seyne-sur-Mer
    La Seyne-sur-Mer is a coastal town in southeastern France on the Mediterranean, historically known for its major shipbuilding industry.
  • E. Roquebrune-Cap-Martin
    Roquebrune-Cap-Martin is a picturesque coastal commune on the French Riviera in southeastern France, known for its medieval village, Mediterranean views, and proximity to Monaco.
  • 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_69ca835edb4481909b4aafb616dc5eb7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f2ef3288190988bd69e8a02e741 completed March 31, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f2793688190a23ab55eba95e177 completed April 3, 2026, 7:41 a.m.
Created at: March 30, 2026, 6:41 p.m.