Triple
T1784425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guinea Station, Virginia |
E39357
|
entity |
| Predicate | hasRailwayFunction |
P19495
|
FINISHED |
| Object | Civil War–era railroad station |
—
|
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: Civil War–era railroad station | Statement: [Guinea Station, Virginia, hasRailwayFunction, Civil War–era railroad station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailwayFunction Context triple: [Guinea Station, Virginia, hasRailwayFunction, Civil War–era railroad station]
-
A.
isElectricRailway
Indicates that a given railway system operates using electric power rather than diesel or other forms of propulsion.
-
B.
hasRailFacility
chosen
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
C.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
-
D.
hasLocomotive
Indicates that one entity possesses or is equipped with a locomotive as part of its composition or operation.
-
E.
hasRailwayZone
Indicates that a location or railway entity falls under the jurisdiction or coverage area of a specific railway zone.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab75457e54819096b8c6ae8c65550c |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61d165688190924962a98e07ff69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.