Triple
T5028140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RC2 |
E113227
|
entity |
| Predicate | usesVariableNumberOfRounds |
P60603
|
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: [RC2, usesVariableNumberOfRounds, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVariableNumberOfRounds Context triple: [RC2, usesVariableNumberOfRounds, true]
-
A.
hasProperRounds
Indicates that an entity is associated with rounds that meet specified standards or criteria for being considered proper or valid.
-
B.
roundCount
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
C.
roundsFor128BitKey
Indicates the number of algorithmic rounds required when operating with a 128-bit cryptographic key.
-
D.
roundsFiredEstimate
Indicates an estimated number of shots or rounds that have been fired in a given context or event.
-
E.
roundsFor192BitKey
Indicates the number of algorithmic processing rounds required when using a 192-bit cryptographic key.
- 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_69bd443775e48190a646ffbfc4334723 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd738d852c8190a122354f1e1f5343 |
completed | March 20, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd724ff2b4819091351cf80d3647a1 |
completed | March 20, 2026, 4:14 p.m. |
Created at: March 20, 2026, 1:36 p.m.