Triple
T21260309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 6 Dress (British Army) |
E523979
|
entity |
| Predicate | hasDressNumber |
P143424
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [No. 6 Dress (British Army), hasDressNumber, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDressNumber Context triple: [No. 6 Dress (British Army), hasDressNumber, 6]
-
A.
hasShirtNumberRole
Indicates that an entity holds a specific shirt number assignment or role, typically within a team or roster context.
-
B.
hasDressCode
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
-
C.
hasDressCircle
Indicates that something (typically a theater or venue) includes or is equipped with a dress circle seating area.
-
D.
usesDressing
Indicates that one entity applies or employs a particular dressing (such as a sauce, covering, or treatment) in relation to another entity or context.
-
E.
hasJersey
Indicates that one entity possesses or is associated with a particular jersey.
- 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_69e0b5156d7881909bd4f83676590715 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735e6a0448190ad412a8fcbbd8ff0 |
completed | April 21, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f9943ed881909ef49045c5bcf6df |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 3:59 p.m.