Triple

T18713719
Position Surface form Disambiguated ID Type / Status
Subject Toulon–Hyères Airport E457581 entity
Predicate locatedIn P40 FINISHED
Object Hyères NE NERFINISHED

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: [Toulon–Hyères Airport, locatedIn, Hyères]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hyères
Context triple: [Toulon–Hyères Airport, locatedIn, Hyères]
  • A. Hyères chosen
    Hyères is a coastal town in southeastern France known for its Mediterranean climate, historic old town, and nearby Golden Islands (Îles d’Hyères).
  • B. Gardanne
    Gardanne is a commune in southern France known for its industrial heritage and location between Marseille and Aix-en-Provence.
  • C. 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.
  • D. Ollioules
    Ollioules is a commune in southeastern France’s Var department, near Toulon on the Mediterranean coast, known for its historic old town and surrounding vineyards and olive groves.
  • E. Villefranche-sur-Mer
    Villefranche-sur-Mer is a picturesque coastal town in southeastern France known for its deep natural harbor, colorful old town, and scenic setting on the Mediterranean Sea.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56ab352b481909b444e7c476898f4 completed April 19, 2026, 11:52 p.m.
Created at: April 10, 2026, 11:50 a.m.