Triple
T28508653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unix crypt(3) |
E721424
|
entity |
| Predicate | originalIterationCount |
P25594
|
FINISHED |
| Object | 25 DES iterations |
—
|
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: 25 DES iterations | Statement: [Unix crypt(3), originalIterationCount, 25 DES iterations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalIterationCount Context triple: [Unix crypt(3), originalIterationCount, 25 DES iterations]
-
A.
iterationsPurpose
Indicates that one or more iterations are performed with the specific goal or intended outcome defined by the associated purpose.
-
B.
repetitionCount
chosen
Indicates the number of times a particular event, action, or pattern is repeated within a given context.
-
C.
hasIteration
Indicates that one entity represents a specific repetition or cycle within the process, sequence, or versioning of another entity.
-
D.
roundCount
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
E.
generationCount
Indicates the number of times a process, entity, or version has been created, iterated, or regenerated within a sequence or lifecycle.
- 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_69f01a5c072081908c7b04bcf6478da9 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fee25dbca481909e6f1c255122b3a8 |
completed | May 9, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69fee1c8915c8190b08b63e42881f1a9 |
completed | May 9, 2026, 7:27 a.m. |
Created at: April 28, 2026, 3:11 a.m.