Triple
T1238094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basilica of Sainte-Anne-de-Beaupré |
E26592
|
entity |
| Predicate | clergyLanguage |
P3115
|
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: [Basilica of Sainte-Anne-de-Beaupré, clergyLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clergyLanguage Context triple: [Basilica of Sainte-Anne-de-Beaupré, clergyLanguage, French]
-
A.
clergyCan
Indicates that members of the clergy are permitted or authorized to perform a specified action or exercise a particular role or function.
-
B.
clergyPractice
Indicates that a member of the clergy engages in, performs, or follows a particular religious practice or ritual.
-
C.
clergyEducation
Indicates that one entity has received formal religious or theological training or education qualifying them for clergy or ministerial roles in relation to another entity or institution.
-
D.
languageOfWorship
chosen
Indicates the language in which religious worship, rituals, or liturgical practices are conducted.
-
E.
positionOnReligiousLanguage
Indicates a stance or viewpoint someone holds regarding how religious language should be understood, interpreted, or used.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf406b988190a12aa26bbcb88d6a |
completed | March 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69a4bb67d52c8190815d6356b79d6ed5 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.