Triple

T23799441
Position Surface form Disambiguated ID Type / Status
Subject Nord (department) E588628 entity
Predicate isMostPopulousDepartmentOf P153601 FINISHED
Object France 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: France | Statement: [Nord (department), isMostPopulousDepartmentOf, France]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isMostPopulousDepartmentOf
Context triple: [Nord (department), isMostPopulousDepartmentOf, France]
  • A. isMostPopulousMunicipalityOf
    Indicates that a municipality has the largest population among all municipalities within the specified administrative area or region.
  • B. hasPopulationRankInDepartment
    Indicates the relative position of an entity’s population size compared to other entities within the same department.
  • C. capitalOfDepartment
    Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
  • D. isMostPopulousDistrictIn
    Indicates that a district has the largest population among all districts within the specified larger region or jurisdiction.
  • E. hasCountryCapitalOfDepartment
    Indicates that a specific country serves as the capital or primary governing nation associated with a particular department.
  • F. None of above. chosen

Provenance (4 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_69e25d15db58819092ac1e6791696fd9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c6dfaae081908be48fa89e625f71 completed April 29, 2026, 8:52 a.m.
PD Predicate disambiguation batch_69f155fe300481909bd617443228df65 completed April 29, 2026, 12:51 a.m.
PDg Predicate description generation batch_69f15adb23d88190ac2632299c26a9b3 completed April 29, 2026, 1:11 a.m.
Created at: April 17, 2026, 7:52 p.m.