Triple

T10364783
Position Surface form Disambiguated ID Type / Status
Subject Arts & Entertainment Network E244223 entity
Predicate laterProgrammingFocus P46383 FINISHED
Object reality-based programming 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: reality-based programming | Statement: [Arts & Entertainment Network, laterProgrammingFocus, reality-based programming]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: laterProgrammingFocus
Context triple: [Arts & Entertainment Network, laterProgrammingFocus, reality-based programming]
  • A. programmingFocus
    Indicates a relationship where an entity’s primary attention, effort, or specialization is directed toward a particular area or aspect of programming.
  • B. originalProgrammingFocus
    Indicates that something’s primary or initial emphasis or specialization is in programming or software development.
  • C. formerProgrammingFocus chosen
    Indicates that an entity previously concentrated on a particular programming-related area or activity, but no longer does so.
  • D. hasProgrammingFocus
    Indicates that something is centered on, specialized in, or primarily concerned with programming.
  • E. programFocus
    Indicates that an educational or training program is primarily oriented around or concentrated on a particular subject, theme, or objective.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e964a53c8190b748e80850e96656 completed April 7, 2026, 11:24 a.m.
PD Predicate disambiguation batch_69d4dfa657f481909cc5cc8fec00ad19 completed April 7, 2026, 10:42 a.m.
Created at: April 6, 2026, noon