Triple
T9832878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto gauge |
E239029
|
entity |
| Predicate | affectsInteroperabilityWith |
P48644
|
FINISHED |
| Object | mainline North American rail network |
—
|
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: mainline North American rail network | Statement: [Toronto gauge, affectsInteroperabilityWith, mainline North American rail network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectsInteroperabilityWith Context triple: [Toronto gauge, affectsInteroperabilityWith, mainline North American rail network]
-
A.
interoperabilityWith
chosen
Indicates that one system, component, or standard can effectively exchange and use information or services with another.
-
B.
areAffectedBy
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
C.
interoperabilityStandard
Indicates that there is a standard or specification enabling different systems, components, or technologies to work together and exchange information seamlessly.
-
D.
requiresCompatibilityWith
Indicates that one entity can only function correctly or be used if it is compatible with another specified entity.
-
E.
affectsProgram
Indicates that one entity produces an influence or change on a program, altering its behavior, state, or outcome.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb336bfc4819084f0d4d6d1867484 |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.