Triple

T459166
Position Surface form Disambiguated ID Type / Status
Subject Master of Information and Data Science E7298 entity
Predicate educationalGoal P12786 FINISHED
Object develop practical data science skills 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: develop practical data science skills | Statement: [Master of Information and Data Science, educationalGoal, develop practical data science skills]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: educationalGoal
Context triple: [Master of Information and Data Science, educationalGoal, develop practical data science skills]
  • A. educationalObjective chosen
    Indicates the intended learning goal, skill, or competency that an educational resource, activity, or program is designed to achieve.
  • B. educationalFocus
    Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
  • C. educationalActivity
    Indicates an action or relationship in which one entity engages in or provides a learning or teaching activity for another.
  • D. 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.
  • E. educationalImpact
    Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
  • 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_69a2e7e5c5bc8190a1dc8178218fba40 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efa4a6208190a8243a0e14f84f52 completed Feb. 28, 2026, 1:37 p.m.
PD Predicate disambiguation batch_69a2ede75b6c81908350103d21f22a03 completed Feb. 28, 2026, 1:30 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.