Triple
T6289853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Earn |
E140987
|
entity |
| Predicate | hasNearbyTransportRoute |
P6208
|
FINISHED |
| Object | A85 road |
—
|
NE NERFINISHED |
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: A85 road | Statement: [River Earn, hasNearbyTransportRoute, A85 road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyTransportRoute Context triple: [River Earn, hasNearbyTransportRoute, A85 road]
-
A.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
B.
hasPublicTransitRoute
Indicates that there exists a public transportation route (such as a bus, train, or tram line) connecting or serving the related entities.
-
C.
transportationNearby
chosen
Indicates that there is a transportation facility or service located close to the referenced entity.
-
D.
hasTransportationRelation
Indicates a relationship in which one entity provides, uses, is connected by, or is otherwise associated with a means or mode of transportation to another entity or location.
-
E.
hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
- 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_69c008cdf2ac8190bb640c94478fb4ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0641a6ecc8190a63be0e3f0344a3f |
completed | March 22, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69c060df0d8881908215575862ef6831 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:26 p.m.