Triple
T13267389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slovakia–Ukraine border |
E315956
|
entity |
| Predicate | hasLanguageOnWesternSide |
P103974
|
FINISHED |
| Object | Slovak |
—
|
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: Slovak | Statement: [Slovakia–Ukraine border, hasLanguageOnWesternSide, Slovak]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOnWesternSide Context triple: [Slovakia–Ukraine border, hasLanguageOnWesternSide, Slovak]
-
A.
hasLanguageOfSide
chosen
Indicates that an entity uses or is associated with a particular language on a specific side or aspect (e.g., one side of a bilingual object or interface).
-
B.
regionalCenterOfWesternSide
Indicates that an entity serves as the primary regional center or hub for the western side of a larger area or region.
-
C.
hasLanguageOnSides
Indicates that an object or medium features written or spoken language present on multiple sides or surfaces.
-
D.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
E.
languageOnAustrianSide
Indicates that a particular language is used or present on the Austrian side of a border, context, or interaction.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:25 p.m.