Triple
T28898685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assembly language |
E732896
|
entity |
| Predicate | isSpecificTo |
P89239
|
FINISHED |
| Object | computer architecture |
—
|
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: computer architecture | Statement: [Assembly language, isSpecificTo, computer architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSpecificTo Context triple: [Assembly language, isSpecificTo, computer architecture]
-
A.
hasSpecificity
Indicates that one entity is defined, characterized, or constrained in a more detailed or narrowly focused way relative to another.
-
B.
isSpecializedFor
chosen
Indicates that one entity is specifically adapted, designed, or focused to perform optimally for a particular function, context, or domain associated with another entity.
-
C.
isSiteSpecific
Indicates that something is designed, intended, or valid only for a particular location, context, or site and does not generally apply elsewhere.
-
D.
requiresSpecificityFor
Indicates that one entity or condition must be defined or described with a higher level of detail or precision in order for another entity, action, or process to be valid or applicable.
-
E.
refersSpecificallyTo
Indicates that one entity makes an explicit, precise reference to another particular entity, distinguishing it from more general or ambiguous references.
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65aa5b40881908123b73bb40b1526 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f6576487e081908d802f1caf59c423 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 8:01 a.m.