Triple
T25348216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autun railway station |
E635609
|
entity |
| Predicate | providesRailConnectionsWithin |
P162094
|
FINISHED |
| Object | Bourgogne-Franche-Comté |
—
|
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: Bourgogne-Franche-Comté | Statement: [Autun railway station, providesRailConnectionsWithin, Bourgogne-Franche-Comté]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesRailConnectionsWithin Context triple: [Autun railway station, providesRailConnectionsWithin, Bourgogne-Franche-Comté]
-
A.
railwayConnectsTo
Indicates that one railway line, track, or network is directly linked or joined to another, allowing trains to move between them.
-
B.
hasPassengerRailConnection
Indicates that there exists a passenger rail service linking one location or transport node to another.
-
C.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
D.
countryRailConnection
Indicates that there is a railway connection or service linking two countries.
-
E.
railConnectionPurpose
Indicates the intended function or goal of a particular rail connection between locations or networks.
- 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_69e75a9ac5d881909387ed766e20cd47 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f622abdfac8190988421c946411d7e |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621fbfc2c8190bfa802d7dc0f6aa4 |
completed | May 2, 2026, 4:10 p.m. |
Created at: April 21, 2026, 1:34 p.m.