Triple

T2135571
Position Surface form Disambiguated ID Type / Status
Subject Chambéry E46643 entity
Predicate hasRiver P165 FINISHED
Object Hyères E244634 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: Hyères | Statement: [Chambéry, hasRiver, Hyères]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hyères
Context triple: [Chambéry, hasRiver, Hyères]
  • A. Frontignan
    Frontignan is a coastal commune in southern France known for its Muscat wine production and Mediterranean setting near Sète.
  • B. Le Beausset chosen
    Le Beausset is a small commune in the Var department of southeastern France, near Toulon in the Provence-Alpes-Côte d'Azur region.
  • C. Fréjus
    Fréjus is a historic town and seaside resort on the French Riviera in southeastern France, known for its Roman ruins and Mediterranean coastline.
  • D. Le Cannet
    Le Cannet is a commune in the Alpes-Maritimes department of southeastern France, located just north of Cannes on the French Riviera.
  • E. Antibes
    Antibes is a historic resort town on the French Riviera known for its Mediterranean coastline, old town, and association with artists such as Pablo Picasso.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbdc4ce8c81908d143d5451681e6a completed March 7, 2026, 5:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae95f487708190b06a536dd20a069a completed March 9, 2026, 9:42 a.m.
Created at: March 4, 2026, 7:44 p.m.