Triple

T17496609
Position Surface form Disambiguated ID Type / Status
Subject France E426076 entity
Predicate hasCity P316 FINISHED
Object Calais 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: Calais | Statement: [France, hasCity, Calais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calais
Context triple: [France, hasCity, Calais]
  • A. Calais chosen
    Calais is a major French port city on the northern coast, serving as one of the primary crossing points between France and England.
  • B. Calais
    Calais is a figure from Greek mythology, one of the winged sons of Boreas who joined Jason and the Argonauts on their legendary voyage.
  • C. Boulogne
    Boulogne is a French football club known for being one of the early professional teams in N’Golo Kanté’s career.
  • D. Cherbourg
    Cherbourg is a major French port city on the Cotentin Peninsula, known for its strategic naval harbor and cross-Channel ferry connections.
  • E. Cherbourg
    Cherbourg is a rural Aboriginal community in southern Queensland, Australia, known for its significant Indigenous history and culture.
  • 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_69d889dccf7481909264a1844a2e9100 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4520e9c8c8190aa955766bc915d26 completed April 19, 2026, 3:54 a.m.
Created at: April 10, 2026, 5:48 a.m.