Triple

T14030352
Position Surface form Disambiguated ID Type / Status
Subject Leonardo Fibonacci E337570 entity
Predicate usedNumeralSystem P5213 FINISHED
Object Hindu–Arabic numeral system 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: Hindu–Arabic numeral system | Statement: [Leonardo Fibonacci, usedNumeralSystem, Hindu–Arabic numeral system]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedNumeralSystem
Context triple: [Leonardo Fibonacci, usedNumeralSystem, Hindu–Arabic numeral system]
  • A. usesNumeralsFrom
    Indicates that one writing system, notation, or representation employs the numeral symbols originating from another system.
  • B. numberingSystemBasedOn
    Indicates that one numbering system is derived from, structured according to, or conceptually dependent on another numbering system.
  • C. hasNumberSystem chosen
    Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
  • D. laterNumberingSystem
    Indicates that one numbering system was adopted or used after another, reflecting a subsequent or more recent scheme of numbering.
  • E. usesRomanNumerals
    Indicates that something represents numbers or sequences using the Roman numeral system rather than standard Arabic digits.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2fa9f8248190930954d609dee5f1 completed April 14, 2026, 12:14 p.m.
PD Predicate disambiguation batch_69de05ab36b48190920efb1869bdb1fe completed April 14, 2026, 9:15 a.m.
Created at: April 9, 2026, 10:20 p.m.