Triple
T5975390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miranda do Douro |
E132971
|
entity |
| Predicate | borderRegionRole |
P67824
|
FINISHED |
| Object | cross-border cultural exchange with Spain |
—
|
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: cross-border cultural exchange with Spain | Statement: [Miranda do Douro, borderRegionRole, cross-border cultural exchange with Spain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderRegionRole Context triple: [Miranda do Douro, borderRegionRole, cross-border cultural exchange with Spain]
-
A.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
-
B.
borderRegionOf
Indicates that one region lies along, touches, or forms part of the boundary of another region.
-
C.
borderRegionsInclude
Indicates that the specified border area encompasses or contains the referenced regions within its boundaries.
-
D.
borderRegionPresence
Indicates the presence or occurrence of something within or along a border region between areas or territories.
-
E.
boundaryReviewRegion
Indicates that a specified region is under consideration or subject to evaluation in a boundary review process.
- 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:04 p.m.