Triple
T33793775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freiburg |
E866007
|
entity |
| Predicate | hasLanguageBorderRole |
P17190
|
FINISHED |
| Object | on French–German linguistic boundary in Switzerland |
—
|
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: on French–German linguistic boundary in Switzerland | Statement: [Freiburg, hasLanguageBorderRole, on French–German linguistic boundary in Switzerland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageBorderRole Context triple: [Freiburg, hasLanguageBorderRole, on French–German linguistic boundary in Switzerland]
-
A.
hasBorderRole
Indicates that an entity holds a specific functional or administrative role related to a border or boundary between regions or jurisdictions.
-
B.
languageAlongBorder
Indicates that a particular language is spoken or prevalent along the border between two regions or entities.
-
C.
hasBordersBy
Indicates that one entity shares a boundary or border with another entity.
-
D.
languageBorderInvolved
chosen
Indicates that a situation, event, or relationship involves or is affected by a boundary between different languages or linguistic communities.
-
E.
hasLanguageOfSide
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).
- 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_69f3498f99f481909cb271f4965a7594 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff0b6bc4a88190bf1d38c6ea26bcdc |
completed | May 9, 2026, 10:24 a.m. |
| PD | Predicate disambiguation | batch_69ff082a22f4819095ded971dbd8ea7b |
completed | May 9, 2026, 10:10 a.m. |
Created at: May 1, 2026, 1:46 a.m.