Triple
T14148668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutschschweiz |
E350616
|
entity |
| Predicate | colloquialSpokenLanguage |
P5203
|
FINISHED |
| Object | Swiss German dialects |
—
|
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: Swiss German dialects | Statement: [Deutschschweiz, colloquialSpokenLanguage, Swiss German dialects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colloquialSpokenLanguage Context triple: [Deutschschweiz, colloquialSpokenLanguage, Swiss German dialects]
-
A.
spokenInCountryColloquialLanguage
Indicates that a language is informally or colloquially spoken within a particular country.
-
B.
hasColloquialVariety
chosen
Indicates that one linguistic form, expression, or variety is an informal, colloquial counterpart or version of another.
-
C.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
D.
typicalLanguageUse
Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
-
E.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61237ef481909374c1f68a2370b7 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:55 a.m.