Triple
T33142877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Väinö Markkanen |
E848204
|
entity |
| Predicate | typeOfShooter |
P17665
|
FINISHED |
| Object | pistol shooter |
—
|
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: pistol shooter | Statement: [Väinö Markkanen, typeOfShooter, pistol shooter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfShooter Context triple: [Väinö Markkanen, typeOfShooter, pistol shooter]
-
A.
shooter
Indicates that one entity performs a shooting action directed at another entity.
-
B.
shootingStyle
chosen
Indicates the characteristic manner or technique with which an entity performs a shooting action (e.g., in sports or photography).
-
C.
primaryShooter
Indicates that the subject is the main individual responsible for firing a weapon in the referenced event or context.
-
D.
gunner
Indicates a person who operates, fires, or is responsible for a gun or artillery weapon in a combat or defense context.
-
E.
shotType
Indicates the specific kind or category of shot used or taken in a given context (e.g., in film, photography, or sports).
- F. None of above.
Provenance (3 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_69f3495961d88190b16ea542c2c5f825 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a00a15604fc8190b1c280794960f3a4 |
completed | May 10, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_6a00a0f7e77881909ac85755ab0e6329 |
completed | May 10, 2026, 3:15 p.m. |
Created at: May 1, 2026, 1:28 a.m.