Triple

T12750595
Position Surface form Disambiguated ID Type / Status
Subject Francofolies de La Rochelle E304718 entity
Predicate organisedIn P8619 FINISHED
Object La Rochelle city center E56822 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: La Rochelle city center | Statement: [Francofolies de La Rochelle, organisedIn, La Rochelle city center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Rochelle city center
Context triple: [Francofolies de La Rochelle, organisedIn, La Rochelle city center]
  • A. La Rochelle chosen
    La Rochelle is a historic French Atlantic port city that became a major stronghold and refuge for Huguenots during the French Wars of Religion.
  • B. Port of La Rochelle
    The Port of La Rochelle is a major Atlantic seaport in western France, known for its commercial shipping, maritime industry, and role as a gateway to the Charente-Maritime region.
  • C. Nantes
    Nantes is a historic port city in western France on the Loire River, known for its maritime heritage, cultural institutions, and vibrant arts scene.
  • D. Saintes
    Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
  • E. Niort
    Niort is a historic city in western France known as an administrative and economic center, particularly for its strong mutual insurance and financial services sector.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96bd75f508190aaae0969f33d1523 completed April 10, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eac829ec8190bea8efdc93151aa0 completed May 3, 2026, 6:27 a.m.
Created at: April 9, 2026, 5:27 p.m.