Triple
T30621207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Despeñaperros Pass |
E779448
|
entity |
| Predicate | railConnectionNearby |
P170255
|
FINISHED |
| Object | Madrid–Seville railway line |
—
|
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: Madrid–Seville railway line | Statement: [Despeñaperros Pass, railConnectionNearby, Madrid–Seville railway line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railConnectionNearby Context triple: [Despeñaperros Pass, railConnectionNearby, Madrid–Seville railway line]
-
A.
providesRailConnectionsWithin
Indicates that an entity offers or facilitates rail transport links connecting locations inside a specified area or region.
-
B.
railwayConnectsTo
Indicates that one railway line, track, or network is directly linked or joined to another, allowing trains to move between them.
-
C.
countryRailConnection
Indicates that there is a railway connection or service linking two countries.
-
D.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
E.
nearestRailwayTerminus
Indicates that one location is the closest railway terminus to another specified place.
- F. None of above. chosen
Provenance (4 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_69f224a3307081909a6dca8ca75dbf48 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68a160374819084d720985f800dfc |
completed | May 2, 2026, 11:34 p.m. |
Created at: April 29, 2026, 8:27 p.m.