Triple
T21175828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 3 Dress (British Army) |
E521808
|
entity |
| Predicate | typeOfJacket |
P15063
|
FINISHED |
| Object | khaki service dress jacket |
—
|
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: khaki service dress jacket | Statement: [No. 3 Dress (British Army), typeOfJacket, khaki service dress jacket]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfJacket Context triple: [No. 3 Dress (British Army), typeOfJacket, khaki service dress jacket]
-
A.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
B.
garmentType
chosen
Indicates the specific kind or category of garment associated with an entity.
-
C.
clothingFeature
Indicates that one entity has a specific clothing-related attribute, detail, or characteristic associated with it.
-
D.
parachuteType
Indicates the specific kind or category of parachute associated with an entity or event.
-
E.
suitType
Indicates the specific category or style of suit associated with an entity (e.g., business suit, spacesuit, wetsuit).
- 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e730197cfc8190bde13453b761886b |
completed | April 21, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3 p.m.