Triple
T11349840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franco-Spanish border wars |
E268811
|
entity |
| Predicate | languageOfBorderRegions |
P77518
|
FINISHED |
| Object | Catalan |
—
|
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: Catalan | Statement: [Franco-Spanish border wars, languageOfBorderRegions, Catalan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfBorderRegions Context triple: [Franco-Spanish border wars, languageOfBorderRegions, Catalan]
-
A.
languageAlongBorder
chosen
Indicates that a particular language is spoken or prevalent along the border between two regions or entities.
-
B.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
C.
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.
-
D.
borderingCountryOfRegion
Indicates that a country shares a land or maritime border with a specified geographic region.
-
E.
isBilingualRegion
Indicates that a region officially uses two languages or has two predominant languages in regular use.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.