Triple
T26856220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oxford University Pistol Club |
E676201
|
entity |
| Predicate | typeOfShooting |
P193772
|
FINISHED |
| Object | precision pistol shooting |
—
|
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: precision pistol shooting | Statement: [Oxford University Pistol Club, typeOfShooting, precision pistol shooting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfShooting Context triple: [Oxford University Pistol Club, typeOfShooting, precision pistol shooting]
-
A.
typeOfKilling
Indicates a specific manner, method, or category of killing that characterizes how the killing was carried out.
-
B.
firearmActionType
Indicates the specific type or category of action performed with or by a firearm (such as firing, loading, carrying, or modifying).
-
C.
numberOfPeopleShot
Indicates the count of individuals who were shot in a particular event or context.
-
D.
shootingOccurredAt
Indicates that a shooting event took place at a specific location.
-
E.
weaponUsedAgainst
Indicates that a particular weapon or instrument is employed in an act of aggression, attack, or harm directed toward a specific target or 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_69eee9b9d7708190a15d7485709ae981 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
| PDg | Predicate description generation | batch_69fd553c01488190b9fda48b4a728f04 |
completed | May 8, 2026, 3:15 a.m. |
Created at: April 27, 2026, 5:21 a.m.