Triple
T37163879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VobSub |
E920744
|
entity |
| Predicate | commonlyUsedInContainer |
P185956
|
FINISHED |
| Object | Matroska |
—
|
NE NERFINISHED |
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: Matroska | Statement: [VobSub, commonlyUsedInContainer, Matroska]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyUsedInContainer Context triple: [VobSub, commonlyUsedInContainer, Matroska]
-
A.
usesContainer
chosen
Indicates that one entity employs or relies on another entity as a container or holding medium for its contents or components.
-
B.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
C.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
D.
isFamouslyUsedIn
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
-
E.
alsoUsedIn
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
- 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_69f76ea0429081908c711b55599eac3c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff2fbae9b48190847eefa1c227d43e |
completed | May 9, 2026, 12:59 p.m. |
| PD | Predicate disambiguation | batch_69ff2f2218048190a32224a648182b5d |
completed | May 9, 2026, 12:57 p.m. |
Created at: May 3, 2026, 4:15 p.m.