Triple
T1001217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia Department of Rail and Public Transportation |
E21605
|
entity |
| Predicate | hasRailFocus |
P5323
|
FINISHED |
| Object | passenger rail |
—
|
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: passenger rail | Statement: [Virginia Department of Rail and Public Transportation, hasRailFocus, passenger rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailFocus Context triple: [Virginia Department of Rail and Public Transportation, hasRailFocus, passenger rail]
-
A.
hasTransitFocus
chosen
Indicates that something is oriented toward, prioritizes, or is primarily concerned with transit or transportation services.
-
B.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
C.
isRailHubFor
Indicates that a location functions as a central node or interchange point within a rail network for the referenced area, routes, or services.
-
D.
hasPrimaryFocus
Indicates that something is the main subject, concern, or area of attention for an entity or activity.
-
E.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fb18b88190ae2d620aaaff4f90 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b1f4f88190822598cfd2a0fd2b |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.