Triple
T19114544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rimfire Sporter Matches |
E467873
|
entity |
| Predicate | hasShootingPosition |
P134481
|
FINISHED |
| Object | prone |
—
|
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: prone | Statement: [Rimfire Sporter Matches, hasShootingPosition, prone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShootingPosition Context triple: [Rimfire Sporter Matches, hasShootingPosition, prone]
-
A.
hasShootingLocation
Indicates that an audiovisual work was filmed or recorded at a particular location.
-
B.
hasPositionOn
Indicates that one entity occupies or holds a specific role, job, or spatial location relative to another entity.
-
C.
positionOnWeapons
Indicates a stance, policy, or viewpoint that an entity holds regarding weapons or weapon-related issues.
-
D.
shotOn
Indicates that one entity fired or took a shot at another entity, typically in a sports or combat context.
-
E.
shotBy
Indicates that one entity fired a projectile or weapon that hit and wounded or killed another entity.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e39617408190b5134918f54f9c52 |
completed | April 20, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe8a06081909fd5c28a33e9f218 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:05 p.m.