Triple

T7584593
Position Surface form Disambiguated ID Type / Status
Subject Var department E179574 entity
Predicate contains P35 FINISHED
Object Le Lavandou E179579 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: Le Lavandou | Statement: [Var department, contains, Le Lavandou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Le Lavandou
Context triple: [Var department, contains, Le Lavandou]
  • A. Le Lavandou chosen
    Le Lavandou is a seaside resort town on the French Riviera in southeastern France, known for its sandy beaches and Mediterranean coastal scenery.
  • B. La Teste-de-Buch
    La Teste-de-Buch is a coastal commune in southwestern France known for its vast forests, Atlantic beaches, and proximity to the Dune of Pilat near Arcachon Bay.
  • C. Le Barcarès
    Le Barcarès is a coastal commune in southern France on the Mediterranean Sea, known for its beaches, marina, and tourism.
  • D. Le Bar-sur-Loup
    Le Bar-sur-Loup is a small historic village in southeastern France’s Alpes-Maritimes department, known for its medieval architecture and scenic setting in the Provence-Alpes-Côte d’Azur region.
  • E. Bonnieux
    Bonnieux is a picturesque hilltop village in southeastern France’s Provence region, known for its historic stone houses, terraced streets, and panoramic views over the Luberon valley.
  • 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_69c69f335248819093c1006f30513708 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f993cd0c8190864f801074625a32 completed March 27, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c861812e08819097fd14fe2b8fee13 completed March 28, 2026, 11:17 p.m.
Created at: March 27, 2026, 3:52 p.m.