Triple
T23980563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernadotte dynasty |
E604494
|
entity |
| Predicate | secondaryLanguageHistoricallyUsed |
P141229
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Bernadotte dynasty, secondaryLanguageHistoricallyUsed, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryLanguageHistoricallyUsed Context triple: [Bernadotte dynasty, secondaryLanguageHistoricallyUsed, French]
-
A.
historicalLanguageOfBearers
chosen
Indicates that the specified language is historically spoken or used by the bearers of a given name, title, or designation.
-
B.
hasMajorityLanguageHistorically
Indicates that a particular language has historically been the predominant or majority language within a given entity or region.
-
C.
languageOfHistoricName
Indicates the language in which a historic or former name of an entity is expressed.
-
D.
historicallySpokenIn
Indicates that a language was used for spoken communication in a particular place or region during a past historical period.
-
E.
historicalLanguage
Indicates that one language is a historical or earlier form/ancestor of another language.
- 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_69e29543f40c819087700b7a272afb60 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d2bd58448190a64e7a9020109229 |
completed | April 29, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:27 p.m.