Triple
T30904894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Georges-de-Bohon |
E787270
|
entity |
| Predicate | hasLocalLanguageTradition |
P141667
|
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: [Saint-Georges-de-Bohon, hasLocalLanguageTradition, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalLanguageTradition Context triple: [Saint-Georges-de-Bohon, hasLocalLanguageTradition, French]
-
A.
hasSecondaryLanguageTradition
Indicates that an entity possesses an additional, non-primary language tradition associated with it, such as in its use, documentation, or cultural context.
-
B.
hasTraditionalLanguageRegion
Indicates the geographic region traditionally associated with the use or origin of a particular language.
-
C.
hasPrimaryTraditionalLanguage
chosen
Indicates that one entity is the main or principal traditional language associated with another entity.
-
D.
hasLinguisticLegacy
Indicates that one entity has left a lasting influence or enduring impact on the language, linguistic practices, or linguistic development associated with another entity.
-
E.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
- 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_69f224bcbcb48190836df847424e4057 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: April 29, 2026, 8:50 p.m.