Triple
T2592834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peninsula rail corridor |
E58161
|
entity |
| Predicate | alsoCarries |
P40070
|
FINISHED |
| Object | intercity passenger trains |
—
|
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: intercity passenger trains | Statement: [Peninsula rail corridor, alsoCarries, intercity passenger trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoCarries Context triple: [Peninsula rail corridor, alsoCarries, intercity passenger trains]
-
A.
carriedBy
Indicates that one entity is physically supported and transported by another entity.
-
B.
alsoCovers
Indicates that something extends its scope or applicability to include an additional subject, area, or case beyond what was originally covered.
-
C.
typicallyHolds
Indicates that a certain relationship or condition generally holds true in typical or normal situations, though not necessarily in all cases.
-
D.
supportsVehicle
Indicates that one entity provides the necessary strength, stability, or structure to bear the weight of a vehicle.
-
E.
relatedVehicle
Indicates that there exists an associated or connected vehicle that has a relevant relationship to the primary 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd426e2d4819081a07920b4d2a1cc |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d344988190a18dd93b13e002e6 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd2baee308190bdaa41ef1f6bc9cc |
completed | March 7, 2026, 7:24 a.m. |
Created at: March 6, 2026, 9:49 p.m.