Triple

T3691206
Position Surface form Disambiguated ID Type / Status
Subject Sugar learning platform E78346 entity
Predicate replacesTraditionalMetaphor P34931 FINISHED
Object desktop metaphor 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: desktop metaphor | Statement: [Sugar learning platform, replacesTraditionalMetaphor, desktop metaphor]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: replacesTraditionalMetaphor
Context triple: [Sugar learning platform, replacesTraditionalMetaphor, desktop metaphor]
  • A. primaryMetaphor
    Indicates a fundamental conceptual mapping where one domain (often concrete or physical) is systematically understood in terms of another (often abstract), forming a basic metaphorical relationship between them.
  • B. keyMetaphor
    Indicates that one entity functions as a central or primary metaphor used to conceptualize, explain, or structure understanding of another entity.
  • C. replacesWord
    Indicates that one word is substituted for another word in a given context or expression.
  • D. modernEquivalent
    Indicates that one entity serves as the contemporary or updated counterpart of another earlier or traditional entity.
  • E. replacesConcept chosen
    Indicates that one concept takes the place of, or supersedes, another concept in a given context or system.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4e783a88190b2837a68b8723a25 completed March 8, 2026, 6:50 p.m.
PD Predicate disambiguation batch_69adb84dc5808190850aa6975cb09e27 completed March 8, 2026, 5:56 p.m.
Created at: March 8, 2026, 3:26 p.m.