Triple

T8584957
Position Surface form Disambiguated ID Type / Status
Subject A Brief History of A Brief History E203281 entity
Predicate hasMetaSubject P83723 FINISHED
Object making of a popular-science classic 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: making of a popular-science classic | Statement: [A Brief History of A Brief History, hasMetaSubject, making of a popular-science classic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMetaSubject
Context triple: [A Brief History of A Brief History, hasMetaSubject, making of a popular-science classic]
  • A. hasMetadata
    Indicates that one entity is associated with descriptive or informational data about another entity.
  • B. hasPrimarySubject
    Indicates that an entity is the main or principal subject associated with another entity or resource.
  • C. hasTypicalSubject
    Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
  • D. hasNotableSubject
    Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
  • E. hasSecondarySubject
    Indicates that an entity is associated with an additional, non-primary subject in a given context or relationship.
  • F. None of above. chosen

Provenance (4 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_69ca8329bb7c8190a63c643730839103 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46c5e8888190b721e791c449b0df completed March 31, 2026, 10:12 p.m.
PD Predicate disambiguation batch_69cc454504448190aaad2af8b17357cd completed March 31, 2026, 10:05 p.m.
PDg Predicate description generation batch_69cc46c330bc8190a9b644078881c6ff completed March 31, 2026, 10:12 p.m.
Created at: March 30, 2026, 6:22 p.m.