Triple
T22157295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop of Baie-Comeau |
E547572
|
entity |
| Predicate | languageOfTerritory |
P10892
|
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: [Bishop of Baie-Comeau, languageOfTerritory, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfTerritory Context triple: [Bishop of Baie-Comeau, languageOfTerritory, French]
-
A.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
B.
regionLanguage
chosen
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
C.
governingCountryLanguage
Indicates that a particular language is officially used or recognized by the governing authorities of a given country.
-
D.
primaryLanguageCountry
Indicates that a given language is the main or officially predominant language used within a particular country.
-
E.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
- 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12a2aadb48190b4d739d1df9529db |
completed | April 28, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69e71b41555881909b8e22718974d527 |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:33 p.m.