Triple

T18178190
Position Surface form Disambiguated ID Type / Status
Subject Deep Learning with Python E435215 entity
Predicate intendedPrerequisites P100 FINISHED
Object basic Python knowledge 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: basic Python knowledge | Statement: [Deep Learning with Python, intendedPrerequisites, basic Python knowledge]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: intendedPrerequisites
Context triple: [Deep Learning with Python, intendedPrerequisites, basic Python knowledge]
  • A. previouslyRequired
    Indicates that one entity was required or necessary before another entity, typically as a prerequisite condition or step.
  • B. requiredTo
    Indicates that one entity has an obligation or necessity to perform an action or satisfy a condition in relation to another entity or context.
  • C. requiresPractice
    Indicates that performing or mastering one entity depends on engaging in repeated practice or training involving another entity.
  • D. requiredBy
    Indicates that one entity depends on or cannot function properly without another entity being present, completed, or satisfied.
  • E. requires chosen
    Indicates that one entity must exist, occur, or be satisfied before another entity can exist, occur, or be carried out.
  • 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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4df5b68f081908aac8210270f1499 completed April 19, 2026, 1:57 p.m.
PD Predicate disambiguation batch_69e4331baeb88190b21f50a98c36c78e completed April 19, 2026, 1:42 a.m.
Created at: April 10, 2026, 10:31 a.m.