Triple
T21191478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Security Association Database |
E522220
|
entity |
| Predicate | containsEntriesFor |
P18283
|
FINISHED |
| Object | unidirectional security associations |
—
|
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: unidirectional security associations | Statement: [Security Association Database, containsEntriesFor, unidirectional security associations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsEntriesFor Context triple: [Security Association Database, containsEntriesFor, unidirectional security associations]
-
A.
hasEntryOn
chosen
Indicates that one entity contains or includes an entry, record, or listing about another entity.
-
B.
hasSubjectEntriesIn
Indicates that a subject is recorded or represented within specific entries of a collection, dataset, or catalog.
-
C.
containsRecord
Indicates that one entity holds, includes, or stores a particular record within it.
-
D.
hasEntryType
Indicates that something is associated with a specific category or type of entry within a system or dataset.
-
E.
hasSubjectEntries
Indicates that an entity is associated with one or more subject-related records or entries.
- 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e733381f288190b3da795f62a39568 |
completed | April 21, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:07 p.m.