Triple
T18281251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIV mode |
E437867
|
entity |
| Predicate | belongsToSubfield |
P131163
|
FINISHED |
| Object | symmetric-key cryptography |
—
|
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: symmetric-key cryptography | Statement: [SIV mode, belongsToSubfield, symmetric-key cryptography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToSubfield Context triple: [SIV mode, belongsToSubfield, symmetric-key cryptography]
-
A.
containsAsSubfield
Indicates that one field or data structure includes another field as a nested or component subfield within it.
-
B.
belongsToSubseries
Indicates that one item is part of, or contained within, a more specific subseries of a larger series or collection.
-
C.
belongsToSubfamily
Indicates that one entity is a member of, or classified within, a specific subfamily of another entity.
-
D.
belongsToSubsector
Indicates that one entity is part of, or classified within, a more specific subsector of a broader sector or industry.
-
E.
hasSubproperty
Indicates that one property is a more specific version of another property, inheriting its meaning and constraints.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50056ea0481908d66bf263ac80c75 |
completed | April 19, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:35 a.m.