Triple

T7584785
Position Surface form Disambiguated ID Type / Status
Subject Le Lavandou E179579 entity
Predicate hasPort P35 FINISHED
Object Le Lavandou marina 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 marina | Statement: [Le Lavandou, hasPort, Le Lavandou marina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Le Lavandou marina
Context triple: [Le Lavandou, hasPort, Le Lavandou marina]
  • 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 Rochelle marina
    La Rochelle marina is a major Atlantic yachting harbor in western France, known as one of Europe’s largest marinas and a popular hub for sailing and nautical tourism.
  • C. La Môle
    La Môle is a small commune in the Var department of southeastern France, situated in the Provence-Alpes-Côte d'Azur region near the French Riviera.
  • D. La Môle
    La Môle is a central fictional nobleman and lover in Alexandre Dumas’s historical novel "Queen Margot," set amid the intrigues and violence of 16th-century France.
  • E. Lignes d’Azur
    Lignes d’Azur is the public transportation network of Nice and its metropolitan area, operating trams and buses across the region.
  • 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_69c86840abc08190b7ca9fb8e2968311 completed March 28, 2026, 11:46 p.m.
Created at: March 27, 2026, 3:52 p.m.