Triple

T11277847
Position Surface form Disambiguated ID Type / Status
Subject Cantal department E266981 entity
Predicate borders P224 FINISHED
Object Lot department E163090 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: Lot department | Statement: [Cantal department, borders, Lot department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lot department
Context triple: [Cantal department, borders, Lot department]
  • A. Lot department chosen
    The Lot department is an administrative region in southwestern France known for its rugged limestone landscapes, medieval villages, and prehistoric cave art.
  • B. Var department
    Var department is an administrative division in the Provence-Alpes-Côte d'Azur region of southeastern France, known for its Mediterranean coastline, resorts, and historic towns.
  • C. Home Department
    The Home Department was a former British government ministry responsible for domestic affairs, which was later reorganized and succeeded by the Home Office.
  • D. Department K
    Department K was a specialized counterintelligence unit within the First Chief Directorate of the KGB, focused primarily on monitoring and combating foreign intelligence activities.
  • E. Department T
    Department T was a specialized technical and scientific intelligence unit within the Soviet KGB’s foreign intelligence apparatus.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e967ebb4819080b09ed3cec44e77 completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f455f0bc8190994c57264f775f60 completed April 19, 2026, 3:27 p.m.
Created at: April 8, 2026, 9:31 p.m.