Triple
T31605460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missy (Fribourg) |
E806470
|
entity |
| Predicate | isPartOfBilingualCanton |
P21622
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Missy (Fribourg), isPartOfBilingualCanton, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfBilingualCanton Context triple: [Missy (Fribourg), isPartOfBilingualCanton, yes]
-
A.
operatesInCanton
Indicates that an entity conducts its activities or has operational presence within a specified canton.
-
B.
isBilingualRegion
chosen
Indicates that a region officially uses two languages or has two predominant languages in regular use.
-
C.
isSharedBetweenCantons
Indicates that something is jointly possessed, administered, or used by two or more cantons.
-
D.
spokenInCanton
Indicates that something (typically a language, phrase, or communication) is expressed using the Cantonese dialect.
-
E.
governingCantonCapital
Indicates that a city serves as the capital and administrative seat of the specified canton.
- 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_69f348d54ccc8190a03b5df9a2b40b25 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
Created at: April 30, 2026, 10:34 p.m.