Triple
T26378138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altera HardCopy family |
E660952
|
entity |
| Predicate | designReuse |
P91997
|
FINISHED |
| Object | reuses FPGA RTL design |
—
|
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: reuses FPGA RTL design | Statement: [Altera HardCopy family, designReuse, reuses FPGA RTL design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designReuse Context triple: [Altera HardCopy family, designReuse, reuses FPGA RTL design]
-
A.
designedForReusability
Indicates that something has been intentionally created or configured so it can be used multiple times without needing to be discarded or fundamentally rebuilt.
-
B.
designUse
Indicates that one entity is used as a design basis, purpose, or intended functional use for another entity.
-
C.
reusability
Indicates that an entity can be used multiple times or in multiple contexts without significant modification or degradation of function.
-
D.
reusedIn
chosen
Indicates that something previously used in one context or instance is used again in another context or instance.
-
E.
maxDesignReuses
Indicates the maximum number of times a given design can be reused within a specified context or system.
- 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_69ee812a698881908d6a58265995fa39 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 26, 2026, 11:02 p.m.