Triple
T1472994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Arabic numerals |
E27176
|
entity |
| Predicate | usedInComputing |
P20866
|
FINISHED |
| Object | supported in Unicode |
—
|
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: supported in Unicode | Statement: [Eastern Arabic numerals, usedInComputing, supported in Unicode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInComputing Context triple: [Eastern Arabic numerals, usedInComputing, supported in Unicode]
-
A.
usedInComputerScience
chosen
Indicates that something is applied, referenced, or has practical relevance within the field of computer science.
-
B.
computes
Indicates that one entity performs a calculation or processing operation to produce a result from given data or inputs.
-
C.
usedPrimarilyIn
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
-
D.
hardwareUsedBy
Indicates that a piece of hardware is utilized or operated by a particular entity (such as a person, system, or organization).
-
E.
usesSoftware
Indicates that one entity employs or operates a particular software application or system to perform tasks or functions.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5dc90e481908a4935f266bc7850 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48350d88190a81bd149103f93e3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.