Triple
T4093892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harvard architecture |
E87766
|
entity |
| Predicate | canReduce |
P9925
|
FINISHED |
| Object | instruction fetch bottlenecks |
—
|
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: instruction fetch bottlenecks | Statement: [Harvard architecture, canReduce, instruction fetch bottlenecks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canReduce Context triple: [Harvard architecture, canReduce, instruction fetch bottlenecks]
-
A.
reduces
chosen
Indicates that one entity causes a decrease in the amount, intensity, degree, or impact of another entity.
-
B.
reducesTo
Indicates that one expression, structure, or state can be transformed or simplified into another, typically more basic or canonical, form.
-
C.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
-
D.
canAlsoBe
Indicates that something has an additional possible state, role, or classification beyond its primary one.
-
E.
canElect
Indicates that one entity has the authority or ability to choose another entity for a position, role, or office through an election process.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefcda2f408190bcf2b64535193162 |
completed | March 9, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69aef909c9c88190b09d48dad325a83c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:40 p.m.