Triple
T7107139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya civilization |
E165616
|
entity |
| Predicate | usedNumberSystem |
P5213
|
FINISHED |
| Object | vigesimal (base-20) 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: vigesimal (base-20) system | Statement: [Maya civilization, usedNumberSystem, vigesimal (base-20) system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedNumberSystem Context triple: [Maya civilization, usedNumberSystem, vigesimal (base-20) system]
-
A.
hasNumberSystem
chosen
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
-
B.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
-
C.
usesPositionalNotation
Indicates that one entity represents numbers using a positional numeral system, where a digit’s value depends on its position.
-
D.
usesDivisionSystem
Indicates that one entity organizes or structures something by applying a particular system of division or categorization.
-
E.
hasNumberDistinction
Indicates that a language or system grammatically distinguishes between different numbers (such as singular, plural, dual, etc.) in its expressions.
- 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_69c6888120f081908f8f01b201dc4a4c |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5b9f13c8190a14898f241ec17a4 |
completed | March 27, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c313e481908b61a23fc89f9332 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:42 p.m.