Triple
T4259998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lovettsville, Virginia |
E96080
|
entity |
| Predicate | crossRiverAccess |
P31589
|
FINISHED |
| Object | Potomac River bridges nearby |
—
|
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: Potomac River bridges nearby | Statement: [Lovettsville, Virginia, crossRiverAccess, Potomac River bridges nearby]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossRiverAccess Context triple: [Lovettsville, Virginia, crossRiverAccess, Potomac River bridges nearby]
-
A.
crossedByRiver
Indicates that a river passes across or through a specified area, feature, or route.
-
B.
crossesWatershed
Indicates that one entity passes from one drainage basin or watershed area into another, traversing the boundary between them.
-
C.
crossingOf
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
-
D.
waterwayAccess
chosen
Indicates that one location has direct access to a waterway (such as a river, canal, or sea route) that can be used for transport, navigation, or related activities.
-
E.
reachedRiver
Indicates that an entity has arrived at or come into contact with a river as a result of movement or travel.
- 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f7fe7348190baed8d214268b756 |
completed | March 12, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69b347f73e008190a908a48ef389945a |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:06 p.m.