Triple
T11930617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMP-2 |
E283899
|
entity |
| Predicate | gunDepression |
P102223
|
FINISHED |
| Object | -5 degrees (approximate) |
—
|
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: -5 degrees (approximate) | Statement: [BMP-2, gunDepression, -5 degrees (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunDepression Context triple: [BMP-2, gunDepression, -5 degrees (approximate)]
-
A.
gun
Indicates that one entity uses, carries, or is associated with a gun in relation to another entity or context.
-
B.
shootingStyle
Indicates the characteristic manner or technique with which an entity performs a shooting action (e.g., in sports or photography).
-
C.
gunType
Indicates the specific category or kind of gun associated with an entity.
-
D.
shootingDiscipline
Indicates the specific type or category of shooting activity or event in which an entity participates or is involved.
-
E.
firearmActionType
Indicates the specific type or category of action performed with or by a firearm (such as firing, loading, carrying, or modifying).
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90303a9a88190a4044e6310ba9b4b |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:45 p.m.