Triple
T19243682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School Bus Replacement and Clean Transportation grants |
E481192
|
entity |
| Predicate | targetsTechnology |
P1482
|
FINISHED |
| Object | zero-emission vehicles |
—
|
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: zero-emission vehicles | Statement: [School Bus Replacement and Clean Transportation grants, targetsTechnology, zero-emission vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsTechnology Context triple: [School Bus Replacement and Clean Transportation grants, targetsTechnology, zero-emission vehicles]
-
A.
focusTechnology
Indicates that an entity is centered on, specializes in, or primarily deals with a particular technology.
-
B.
technologyType
chosen
Indicates the specific kind or category of technology associated with an entity or relationship.
-
C.
technologyBasis
Indicates that one entity is founded on, enabled by, or fundamentally relies upon the technology provided or represented by another entity.
-
D.
technologyUsedBy
Indicates that a particular technology is employed or utilized by a specified entity.
-
E.
technologyField
Indicates the area or domain of technology in which an entity is involved, specialized, or categorized.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faf3018881909ef866616c45ff2e |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:27 p.m.