Triple

T16541637
Position Surface form Disambiguated ID Type / Status
Subject German universities of applied sciences E401831 entity
Predicate typicalFieldOfStudy P2582 FINISHED
Object engineering 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: engineering | Statement: [German universities of applied sciences, typicalFieldOfStudy, engineering]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalFieldOfStudy
Context triple: [German universities of applied sciences, typicalFieldOfStudy, engineering]
  • A. offersFieldOfStudy chosen
    Indicates that an institution or program provides a particular field of study as an available area of academic focus.
  • B. hasSubjectOfStudy
    Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
  • C. dimensionOfStudy
    Indicates the specific field, aspect, or perspective that characterizes or structures a particular study or research activity.
  • D. regionOfStudy
    Indicates the academic or research area that is the focus of someone’s study or investigation.
  • E. studiesIn
    Indicates that a person is enrolled as a student at, and pursues their studies within, a particular educational institution or program.
  • 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_69d88384bc30819084229e7dcdc39a41 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3455cf4b88190b3c9e93e158a7686 completed April 18, 2026, 8:48 a.m.
PD Predicate disambiguation batch_69e2969fab208190ad64164d24748c45 completed April 17, 2026, 8:22 p.m.
Created at: April 10, 2026, 5:15 a.m.