Triple
T19520006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fabrique de la paroisse Notre‑Dame de Montréal |
E488377
|
entity |
| Predicate | usesNameInLanguage |
P15
|
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: [Fabrique de la paroisse Notre‑Dame de Montréal, usesNameInLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNameInLanguage Context triple: [Fabrique de la paroisse Notre‑Dame de Montréal, usesNameInLanguage, French]
-
A.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
-
B.
languageOfWorkOrName
chosen
Indicates the language in which a work is created or a name is expressed.
-
C.
usesNameForm
Indicates that one entity adopts or applies a particular standardized form or variant of a name associated with another entity.
-
D.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
E.
usesNameDueTo
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6359feb808190ba94563831adc720 |
completed | April 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7d0da88190aabf8b5799691fb1 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.