Triple
T1919175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quebec Civil Code |
E40085
|
entity |
| Predicate | legalLanguage |
P11896
|
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: [Quebec Civil Code, legalLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalLanguage Context triple: [Quebec Civil Code, legalLanguage, French]
-
A.
legalContext
Indicates that the relationship or action occurs within, is shaped by, or is relevant to a specific legal framework, proceeding, or set of legal norms.
-
B.
legalProtectionOfLanguage
chosen
Indicates that a language is safeguarded or regulated by formal legal measures, such as laws, policies, or constitutional provisions.
-
C.
legalBackground
Indicates that an entity has education, training, or experience related to law or the legal profession.
-
D.
legalConcept
Indicates a relationship where something is classified or treated as a concept defined and governed by law or legal theory.
-
E.
policyLanguage
Indicates the specific wording or formulation used within a policy to express its rules, conditions, or provisions.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb211eda88190865de7a0522a453d |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafed2ab481908920334e77b1021b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.