Triple
T22557913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany and Italy |
E557735
|
entity |
| Predicate | haveExtensiveRailConnections |
P13914
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Germany and Italy, haveExtensiveRailConnections, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveExtensiveRailConnections Context triple: [Germany and Italy, haveExtensiveRailConnections, true]
-
A.
hasMajorRailLinksTo
chosen
Indicates that there are significant railway connections or routes between two locations.
-
B.
hasPassengerRailConnection
Indicates that there exists a passenger rail service linking one location or transport node to another.
-
C.
hasMajorRailwayStation
Indicates that a place contains or is served by a principal railway station that functions as a major hub for rail transport.
-
D.
hasGoodPublicTransportConnections
Indicates that an entity is well served by public transportation options, providing convenient and efficient connections to other locations.
-
E.
hasMajorRailCorridor
Indicates that a location or region is traversed by a primary, high-capacity railway route used for significant passenger or freight transport.
- 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f7b06e08190b3ca82a783965942 |
completed | April 29, 2026, 1:31 a.m. |
| PD | Predicate disambiguation | batch_69e898cb3fb48190add6ab24a2df5822 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:52 p.m.