Triple
T21747747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Navy dress uniform |
E536829
|
entity |
| Predicate | hasSeasonalVariant |
P61951
|
FINISHED |
| Object | winter uniform |
—
|
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: winter uniform | Statement: [U.S. Navy dress uniform, hasSeasonalVariant, winter uniform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalVariant Context triple: [U.S. Navy dress uniform, hasSeasonalVariant, winter uniform]
-
A.
hasSeasonalCollections
Indicates that an entity offers or maintains collections that vary according to specific seasons or times of year.
-
B.
hasSeasonalStatus
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
-
C.
hasSeasonalHighlight
Indicates that something features a notable or emphasized aspect during a particular season or time of year.
-
D.
hasSeasonalCounterpart
chosen
Indicates that one entity corresponds to another entity that appears or is relevant in a different season as its counterpart.
-
E.
hasSeasonalText
Indicates that an entity is associated with text that is specific to or varies by a particular season or time of year.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a77e19c81909bf26f96aa41a7ce |
completed | April 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.