Triple
T33324774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AAA School Safety Patrol |
E853233
|
entity |
| Predicate | hasTrainingTopic |
P199322
|
FINISHED |
| Object | traffic signs and signals |
—
|
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: traffic signs and signals | Statement: [AAA School Safety Patrol, hasTrainingTopic, traffic signs and signals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingTopic Context triple: [AAA School Safety Patrol, hasTrainingTopic, traffic signs and signals]
-
A.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
B.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
C.
hasTrainingTrack
Indicates that an entity is associated with or assigned to a specific training track or program.
-
D.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
E.
hasTutorialIn
Indicates that one entity provides or includes a tutorial within the context or medium of another 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_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff2eb19ad88190915fbbe08e8bc84e |
completed | May 9, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69ff2db5dd608190b7b7ba95f19c276c |
completed | May 9, 2026, 12:51 p.m. |
| PDg | Predicate description generation | batch_69ff2eb0c0888190b0e05a03bf06d388 |
completed | May 9, 2026, 12:55 p.m. |
Created at: May 1, 2026, 1:33 a.m.