Triple
T28353991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .577 Snider |
E718173
|
entity |
| Predicate | typicalBulletType |
P202508
|
FINISHED |
| Object | lead bullet |
—
|
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: lead bullet | Statement: [.577 Snider, typicalBulletType, lead bullet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBulletType Context triple: [.577 Snider, typicalBulletType, lead bullet]
-
A.
typicalItem
Indicates that an item is a representative or characteristic example of a broader category, class, or set.
-
B.
typicalWeapon
Indicates that the object is a weapon commonly or characteristically used by the subject.
-
C.
typicalOption
Indicates that one option is considered standard, common, or most representative among a set of possible options.
-
D.
typicalBillet
Indicates that something serves as a standard or characteristic billet or assignment for a given role, context, or entity.
-
E.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
- 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_69eff6ec27b481908c8d7b86c47893d9 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_6a008c77d4dc8190b342d7407eaf48fa |
completed | May 10, 2026, 1:47 p.m. |
| PD | Predicate disambiguation | batch_6a008c18531c8190bbe883b73e6d023f |
completed | May 10, 2026, 1:46 p.m. |
| PDg | Predicate description generation | batch_6a008c770df481908fe58b265fba06a3 |
completed | May 10, 2026, 1:47 p.m. |
Created at: April 28, 2026, 12:48 a.m.