Triple

T2516117
Position Surface form Disambiguated ID Type / Status
Subject La Brède E55415 entity
Predicate hasRegionCode P3446 FINISHED
Object FR-NAQ
FR-NAQ is the regional code for Nouvelle-Aquitaine, an administrative region in southwestern France.
 E275822 NE FINISHED

How this triple was built (4 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: FR-NAQ | Statement: [La Brède, hasRegionCode, FR-NAQ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FR-NAQ
Context triple: [La Brède, hasRegionCode, FR-NAQ]
  • A. FR3
    FR3 was a former French public television channel and network that later became part of France Télévisions.
  • B. FR-26
    FR-26 is the ISO 3166-2 code designating the Drôme department in southeastern France.
  • C. Fran
    Fran is a common shortened given name, typically used as a diminutive of Frances or Francis.
  • D. FR-77
    FR-77 is the ISO 3166-2 code designating the French department of Seine-et-Marne in the Île-de-France region.
  • E. NAFU
    NAFU (North American Football Union) is a regional football governing body in North America that oversees and organizes competitions and development for member national teams within the CONCACAF structure.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: FR-NAQ
Triple: [La Brède, hasRegionCode, FR-NAQ]
Generated description
FR-NAQ is the regional code for Nouvelle-Aquitaine, an administrative region in southwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FR-NAQ
Target entity description: FR-NAQ is the regional code for Nouvelle-Aquitaine, an administrative region in southwestern France.
  • A. FR3
    FR3 was a former French public television channel and network that later became part of France Télévisions.
  • B. FR-26
    FR-26 is the ISO 3166-2 code designating the Drôme department in southeastern France.
  • C. Fran
    Fran is a common shortened given name, typically used as a diminutive of Frances or Francis.
  • D. FR-77
    FR-77 is the ISO 3166-2 code designating the French department of Seine-et-Marne in the Île-de-France region.
  • E. NAFU
    NAFU (North American Football Union) is a regional football governing body in North America that oversees and organizes competitions and development for member national teams within the CONCACAF structure.
  • F. None of above. chosen

Provenance (5 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_69ab49e4749c8190813311efd1630f1b completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd20f8d0c8190bfdcb99a12f59d59 completed March 7, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b9aa5cc81908c2e09ce18f2e98e completed March 9, 2026, 8:20 p.m.
NEDg Description generation batch_69af508c28f48190afc4aa1bc3c9adf3 completed March 9, 2026, 10:58 p.m.
NED2 Entity disambiguation (via description) batch_69af5155f85081908dd4a1859d0f7907 completed March 9, 2026, 11:01 p.m.
Created at: March 6, 2026, 9:46 p.m.