Triple

T13589208
Position Surface form Disambiguated ID Type / Status
Subject French preparatory classes E324646 entity
Predicate leadsToQualification P106510 FINISHED
Object eligibility for grandes écoles diplomas LITERAL 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: eligibility for grandes écoles diplomas | Statement: [French preparatory classes, leadsToQualification, eligibility for grandes écoles diplomas]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: leadsToQualification
Context triple: [French preparatory classes, leadsToQualification, eligibility for grandes écoles diplomas]
  • A. leadsInto
    Indicates that one entity serves as an entry or transition point that directly connects or opens into another entity.
  • B. hasQualification
    Indicates that an entity possesses a specific qualification, credential, or competency.
  • C. helpsLead
    Indicates that one entity assists or contributes to another entity’s act of leading or guiding.
  • D. qualifyingFor chosen
    Indicates that one entity meets the necessary conditions or criteria to be eligible for another entity, status, or action.
  • E. providedQualificationFor
    Indicates that one entity supplied or granted a qualification, credential, or certification that another entity possesses or uses.
  • F. None of above.

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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb055cc98819091fab597b69e5e3e completed April 12, 2026, 2:46 p.m.
PD Predicate disambiguation batch_69dbae18eaf48190809e8b365856cde9 completed April 12, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:49 p.m.