Triple
T7415100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AddRoundKey |
E171108
|
entity |
| Predicate | appliedBytewise |
P76812
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [AddRoundKey, appliedBytewise, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedBytewise Context triple: [AddRoundKey, appliedBytewise, true]
-
A.
appliedBy
Indicates that an action, process, or treatment is carried out or executed by a particular agent or entity.
-
B.
appliedAs
Indicates that one entity submitted itself or was put forward for consideration in a particular role, position, or context relative to another entity.
-
C.
appliedTest
Indicates that a test has been administered or carried out on a particular subject or object.
-
D.
appliesAt
Indicates that an action, rule, or condition is relevant to or in effect at a specific location, context, or point in time.
-
E.
appliesOver
Indicates that one entity’s effect, rule, or condition extends across or is valid for a specified range, domain, or set of entities.
- F. None of above. chosen
Provenance (4 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2c643248190a387abba2f482b25 |
completed | March 27, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1c3307481909a7f6bb69d4fddac |
completed | March 27, 2026, 9:08 p.m. |
Created at: March 27, 2026, 3:11 p.m.