Triple

T35135838
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Medicine, University of Maiduguri E1014568 entity
Predicate offersTrainingSetting P76860 FINISHED
Object teaching hospital 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: teaching hospital | Statement: [Faculty of Medicine, University of Maiduguri, offersTrainingSetting, teaching hospital]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: offersTrainingSetting
Context triple: [Faculty of Medicine, University of Maiduguri, offersTrainingSetting, teaching hospital]
  • A. providesTrainingSetting chosen
    Indicates that one entity serves as the environment or context in which training or educational activities are conducted for another entity.
  • B. offersTrainingLevel
    Indicates that one entity provides or makes available a specific level or tier of training to another entity.
  • C. offersApprenticeshipTraining
    Indicates that one entity provides apprenticeship-based training opportunities or programs to another entity.
  • D. offersEducationIn
    Indicates that an entity provides or delivers educational programs, courses, or instruction in a specified field, subject, or area.
  • E. offersCertificationPreparationFor
    Indicates that an entity provides training or resources specifically designed to prepare individuals for obtaining a particular certification.
  • 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_69f76dd9c1848190af70d4882a2c1ad7 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fe610e1f6881908f10070ba64643cf completed May 8, 2026, 10:17 p.m.
PD Predicate disambiguation batch_69fe604c6c008190ad659e9b9fa82f7b completed May 8, 2026, 10:14 p.m.
Created at: May 3, 2026, 4:02 p.m.