Triple
T11988897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catalan Countries |
E285352
|
entity |
| Predicate | borderLanguageAreas |
P77518
|
FINISHED |
| Object | Spanish-speaking regions |
—
|
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: Spanish-speaking regions | Statement: [Catalan Countries, borderLanguageAreas, Spanish-speaking regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderLanguageAreas Context triple: [Catalan Countries, borderLanguageAreas, Spanish-speaking regions]
-
A.
borderDialectOf
Indicates a dialect that is spoken in a border area and is linguistically associated with or derived from a particular neighboring language or dialect.
-
B.
languageAlongBorder
chosen
Indicates that a particular language is spoken or prevalent along the border between two regions or entities.
-
C.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
-
D.
borderRegionsInclude
Indicates that the specified border area encompasses or contains the referenced regions within its boundaries.
-
E.
borderRegionOf
Indicates that one region lies along, touches, or forms part of the boundary of another region.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903ae28708190a826bad1624343eb |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.