Triple

T366749
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Dental Medicine, University of Havana E7977 entity
Predicate educationalObjective P12786 FINISHED
Object training dentists 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: training dentists | Statement: [Faculty of Dental Medicine, University of Havana, educationalObjective, training dentists]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: educationalObjective
Context triple: [Faculty of Dental Medicine, University of Havana, educationalObjective, training dentists]
  • A. educationalFocus
    Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
  • B. educationalModel
    Indicates that one entity serves as an educational model, framework, or paradigm that guides or structures the teaching, learning, or training practices of another entity.
  • C. educationalApproach
    Indicates the method, strategy, or philosophy used to guide teaching and learning within an educational context.
  • D. hasEducationalMission
    Indicates that an entity is responsible for or engaged in carrying out an educational purpose, goal, or function.
  • E. educates
    Indicates that one entity provides instruction, knowledge, or training to another entity.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebe92c7c8190b49af2b2b461eacc completed Feb. 28, 2026, 1:21 p.m.
PD Predicate disambiguation batch_69a2e95dbb208190b277fc5352a4ee84 completed Feb. 28, 2026, 1:10 p.m.
PDg Predicate description generation batch_69a2eafc8da88190b4a05182f4384442 completed Feb. 28, 2026, 1:17 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.