Triple
T27860010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Cyr cadet sword |
E704197
|
entity |
| Predicate | carriedAs |
P166464
|
FINISHED |
| Object | sidearm on dress 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: sidearm on dress uniform | Statement: [Saint-Cyr cadet sword, carriedAs, sidearm on dress uniform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carriedAs Context triple: [Saint-Cyr cadet sword, carriedAs, sidearm on dress uniform]
-
A.
carriedFor
Indicates that one entity transported or bore another entity on behalf of or for the benefit of that other entity.
-
B.
carriedTo
Indicates that one entity transported or conveyed another entity from one place to another.
-
C.
carriedBy
Indicates that one entity is physically supported and transported by another entity.
-
D.
carriedFrom
Indicates that something was transported or moved away starting from a specified source location or origin.
-
E.
carriedProp
Indicates that one entity transported or bore another entity as a carried object or property.
- 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_69ef840e614c8190a88cf9638c14a265 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6622808b48190bbabcc75288ab031 |
completed | May 2, 2026, 8:44 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f6617a7e7c81908cfac4a2250797ee |
completed | May 2, 2026, 8:41 p.m. |
Created at: April 27, 2026, 6:17 p.m.