Triple

T6757819
Position Surface form Disambiguated ID Type / Status
Subject Luberon massif E154506 entity
Predicate contains P35 FINISHED
Object Lourmarin E307114 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: Lourmarin | Statement: [Luberon massif, contains, Lourmarin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lourmarin
Context triple: [Luberon massif, contains, Lourmarin]
  • A. Marignane
    Marignane is a commune in southern France near Marseille, known for hosting Marseille Provence Airport and its proximity to the Mediterranean coast.
  • B. Aigues-Mortes
    Aigues-Mortes is a historic fortified town in southern France, renowned for its well-preserved medieval walls and proximity to the salt marshes of the Camargue.
  • C. Lourmarin, France chosen
    Lourmarin, France is a picturesque Provençal village in the Luberon region of southeastern France, known for its Renaissance château, vibrant cultural life, and association with writer Albert Camus.
  • D. 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.
  • E. Frontignan
    Frontignan is a coastal commune in southern France known for its Muscat wine production and Mediterranean setting near Sète.
  • 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_69c6880fd5808190be684854081e27dd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1f90b6c8190b4a17a23aa9ba0fb completed March 27, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748a267488190bc7c5da9503b78c9 completed March 28, 2026, 3:18 a.m.
Created at: March 27, 2026, 2:11 p.m.