Triple
T21175829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 3 Dress (British Army) |
E521808
|
entity |
| Predicate | typeOfTrousers |
P15063
|
FINISHED |
| Object | matching khaki service dress trousers |
—
|
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: matching khaki service dress trousers | Statement: [No. 3 Dress (British Army), typeOfTrousers, matching khaki service dress trousers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfTrousers Context triple: [No. 3 Dress (British Army), typeOfTrousers, matching khaki service dress trousers]
-
A.
garmentType
chosen
Indicates the specific kind or category of garment associated with an entity.
-
B.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
C.
hasSkirtType
Indicates that an entity is associated with or characterized by a specific type or style of skirt.
-
D.
colorOfApparel
Indicates the specific color attribute associated with a piece of apparel or clothing item.
-
E.
bandType
Indicates the specific kind or category of band that an entity belongs to or is associated with.
- 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.