Triple
T19494522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PKCS #12 |
E487734
|
entity |
| Predicate | supportsMultipleObjects |
P136126
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [PKCS #12, supportsMultipleObjects, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsMultipleObjects Context triple: [PKCS #12, supportsMultipleObjects, yes]
-
A.
supportsMultipleFiles
Indicates that the subject is capable of handling, processing, or operating on more than one file at the same time.
-
B.
supportsMultipleOnSameTarget
Indicates that the relationship or action can be applied multiple times concurrently to the same target entity.
-
C.
supportsMultipleMatches
Indicates that the relationship or operation can involve or return more than one matching counterpart rather than being limited to a single match.
-
D.
supportsMultipleRanges
Indicates that an entity can handle, accept, or operate over more than one distinct range of values or intervals.
-
E.
hasMultiple
Indicates that an entity is associated with more than one instance or occurrence of another related entity.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63490c16481908423e304d82722d7 |
completed | April 20, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7883308190b73912a71a35a835 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004d3a708190a1c13c8f644f3926 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.