Triple
T23533751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Traffic Court |
E576636
|
entity |
| Predicate | hearsApplications |
P153145
|
FINISHED |
| Object | applications related to driving licence disqualification |
—
|
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: applications related to driving licence disqualification | Statement: [Traffic Court, hearsApplications, applications related to driving licence disqualification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hearsApplications Context triple: [Traffic Court, hearsApplications, applications related to driving licence disqualification]
-
A.
hasApp
Indicates that an entity possesses, provides, or is associated with a particular application.
-
B.
applicationRequirement
Indicates that one entity specifies a condition or prerequisite that must be met for the use, approval, or execution of another entity or process.
-
C.
canHear
Indicates that one entity is able to perceive sounds produced by another entity.
-
D.
hears
Indicates that one entity perceives or detects sounds produced by another entity or source.
-
E.
notableApp
Indicates that an application is recognized as significant, prominent, or noteworthy in some context.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae14ae3c8190aa2714ea07a4658a |
completed | April 29, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
| PDg | Predicate description generation | batch_69f12760784c8190aaeff002ef31febe |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 17, 2026, 6:10 p.m.