Triple
T3131499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vila Real de Santo António railway station |
E65422
|
entity |
| Predicate | regionEndpoint |
P36184
|
FINISHED |
| Object | eastern Algarve rail network |
—
|
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: eastern Algarve rail network | Statement: [Vila Real de Santo António railway station, regionEndpoint, eastern Algarve rail network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionEndpoint Context triple: [Vila Real de Santo António railway station, regionEndpoint, eastern Algarve rail network]
-
A.
endpointRegion
Indicates that one entity serves as the geographic or logical region in which the other entity’s endpoint is located or configured.
-
B.
endPoint
Indicates the terminal location, limit, or final state reached by an object, process, or path in a given relationship or action.
-
C.
hasEndpointCity
Indicates that a route, connection, or path terminates at a particular city as one of its endpoints.
-
D.
terminusRegion
chosen
Indicates the region or area where something (such as a route, line, or process) ends or reaches its final point.
-
E.
endPointExample
Indicates that something serves as a representative or illustrative instance of a particular endpoint.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada54b0e688190b691771f17f4c721 |
completed | March 8, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69ad9df62e548190b053e1478deed467 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:04 p.m.