Triple
T14030353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonardo Fibonacci |
E337570
|
entity |
| Predicate | promotedNumeralSystem |
P96282
|
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, promotedNumeralSystem, Hindu–Arabic numeral system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: promotedNumeralSystem Context triple: [Leonardo Fibonacci, promotedNumeralSystem, Hindu–Arabic numeral system]
-
A.
laterNumberingSystem
chosen
Indicates that one numbering system was adopted or used after another, reflecting a subsequent or more recent scheme of numbering.
-
B.
numberingSystemBasedOn
Indicates that one numbering system is derived from, structured according to, or conceptually dependent on another numbering system.
-
C.
usesNumeralsFrom
Indicates that one writing system, notation, or representation employs the numeral symbols originating from another system.
-
D.
hasNumberSystem
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
-
E.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
- 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.