Triple

T16194144
Position Surface form Disambiguated ID Type / Status
Subject Siege of Boulogne (1544) E393017 entity
Predicate hasLocation P40 FINISHED
Object Boulogne E122723 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: Boulogne | Statement: [Siege of Boulogne (1544), hasLocation, Boulogne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boulogne
Context triple: [Siege of Boulogne (1544), hasLocation, Boulogne]
  • A. Boulogne
    Boulogne is a French football club known for being one of the early professional teams in N’Golo Kanté’s career.
  • B. Boulogne-sur-Gesse
    Boulogne-sur-Gesse is a small commune in southwestern France, known for its rural setting and location in the Haute-Garonne department of the Occitanie region.
  • C. Boulogne-sur-Mer chosen
    Boulogne-sur-Mer is a coastal city and major fishing port in northern France, located on the English Channel in the Pas-de-Calais department.
  • D. de Boulogne
    de Boulogne is the surname of the French Baroque painter Valentin de Boulogne, known for his dramatic Caravaggesque style.
  • E. Boulogne-sur-Seine
    Boulogne-sur-Seine was a former commune in the western suburbs of Paris, France, now part of Boulogne-Billancourt, known historically as a residential and industrial area along the Seine River.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222d851188190b2452d165e4fc4bd completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffff0bfd08819083afc4bea1b99aad completed May 10, 2026, 3:44 a.m.
Created at: April 10, 2026, 5:02 a.m.