Triple

T20407246
Position Surface form Disambiguated ID Type / Status
Subject Celje E500500 entity
Predicate hasTwinTown P919 FINISHED
Object La Rochelle 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: La Rochelle | Statement: [Celje, hasTwinTown, La Rochelle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Rochelle
Context triple: [Celje, hasTwinTown, La Rochelle]
  • 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. Toulon
    Toulon is a major port city on France’s Mediterranean coast that serves as the principal base of the French Navy.
  • 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. 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.
  • E. Floirac
    Floirac is a suburban commune in southwestern France located near the city of Bordeaux, known for its residential areas and proximity to the Garonne River.
  • 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_69e0b4a81bec8190b69adfdc1336a015 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67993dc7081908ebd54ec92e712ea completed April 20, 2026, 7:08 p.m.
Created at: April 16, 2026, 11:29 a.m.