Triple
T9659714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Numbers in Color |
E233556
|
entity |
| Predicate | numericalSystem |
P5213
|
FINISHED |
| Object | Arabic numerals |
—
|
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: Arabic numerals | Statement: [Numbers in Color, numericalSystem, Arabic numerals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numericalSystem Context triple: [Numbers in Color, numericalSystem, Arabic numerals]
-
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.
usesNumeralsFrom
Indicates that one writing system, notation, or representation employs the numeral symbols originating from another system.
-
D.
numeralsRangePerPosition
Indicates the allowed range of numeral values that can appear in each positional place within a number representation.
-
E.
hasNumeral
Indicates that one entity is associated with a numeral representation or numeric symbol of 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_69ca848c1ba88190b84b410cd14627fc |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c08d0d0819086426ad6891b18db |
completed | April 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b3239c8190b3ae3b9bd121e4bd |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:14 p.m.