Triple
T22438883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bond Arms Texas Defender |
E554699
|
entity |
| Predicate | legalClassificationUS |
P20157
|
FINISHED |
| Object | pistol |
—
|
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 | Statement: [Bond Arms Texas Defender, legalClassificationUS, pistol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalClassificationUS Context triple: [Bond Arms Texas Defender, legalClassificationUS, pistol]
-
A.
legalExceptionUnitedStates
Indicates that the usual legal rule or requirement does not apply in the United States due to a specific statutory, regulatory, or judicially recognized exception.
-
B.
juridicalCategory
Indicates the legal classification or status under which an entity or relationship is formally recognized in a juridical system.
-
C.
legalClassificationInJapan
Indicates how something is categorized or defined under Japanese law.
-
D.
classificationByUS
chosen
Indicates a relationship where an entity is assigned a category, status, or type according to a classification system defined or used by the United States.
-
E.
legalCodeName
Indicates that one entity is the official legal code designation or name assigned to another entity within a legal or regulatory system.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae01bd08190aee5141f4c0848bc |
completed | April 29, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.