Triple
T359760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cross Border Xpress |
E7821
|
entity |
| Predicate | notFor |
P7974
|
FINISHED |
| Object | vehicular traffic |
—
|
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: vehicular traffic | Statement: [Cross Border Xpress, notFor, vehicular traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notFor Context triple: [Cross Border Xpress, notFor, vehicular traffic]
-
A.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
-
B.
notTypicallyUsedFor
chosen
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
C.
notFunction
Indicates that the specified entity does not serve as a function or is not used in a functional role within the given context.
-
D.
doesNotStandFor
Indicates that one entity does not represent, symbolize, or act on behalf of another entity in any capacity.
-
E.
doesNotAbolish
Indicates that one entity, action, or law does not eliminate, revoke, or put an end to another.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebccb8d88190a31f7c443a0c8566 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95aeed48190b5e48865cc964938 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.