Triple
T19956704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greeba |
E479701
|
entity |
| Predicate | hasNearbyRailwayFeature |
P25143
|
FINISHED |
| Object | former Douglas–Peel railway line |
—
|
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: former Douglas–Peel railway line | Statement: [Greeba, hasNearbyRailwayFeature, former Douglas–Peel railway line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyRailwayFeature Context triple: [Greeba, hasNearbyRailwayFeature, former Douglas–Peel railway line]
-
A.
hasNearbyRailway
chosen
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
B.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
C.
nearestRailwayLine
Indicates that one railway line is the closest in distance to a given location or feature compared to all other railway lines.
-
D.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
E.
nearestRailwayTerminus
Indicates that one location is the closest railway terminus to another specified place.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65af08e008190a3a1b807b638a99e |
completed | April 20, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.