Triple
T22604604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Code Division Multiple Access |
E566521
|
entity |
| Predicate | distinguishesUsersBy |
P107472
|
FINISHED |
| Object | unique codes |
—
|
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: unique codes | Statement: [Code Division Multiple Access, distinguishesUsersBy, unique codes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinguishesUsersBy Context triple: [Code Division Multiple Access, distinguishesUsersBy, unique codes]
-
A.
isDistinguishedBy
Indicates that one entity is characterized or set apart from others by a particular feature, quality, or attribute.
-
B.
identifiedUsing
chosen
Indicates that one entity was recognized, distinguished, or determined by means of a specified method, tool, or identifier.
-
C.
uniformDistinction
Indicates that a clear and consistent difference is maintained between two or more entities within a given context.
-
D.
distinguishingTrait
Indicates that a particular characteristic or feature uniquely differentiates one entity from another.
-
E.
hasRegisterDistinction
Indicates that there is a meaningful difference in language register (e.g., formality or style) between the related linguistic forms or usages.
- 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_69e245884860819081046ce07d5872c4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f162709d808190af83837104a190f9 |
completed | April 29, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:52 p.m.