Triple
T3706057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuiseaux |
E80895
|
entity |
| Predicate | lawSystem |
P605
|
FINISHED |
| Object | French law |
—
|
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 law | Statement: [Cuiseaux, lawSystem, French law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawSystem Context triple: [Cuiseaux, lawSystem, French law]
-
A.
legalSystem
chosen
Indicates the formal framework of laws, rules, and institutions that governs how legal matters are defined, interpreted, and enforced within a society or jurisdiction.
-
B.
law
Indicates that one entity establishes, embodies, or enforces a rule or system of rules governing the behavior or relations of another entity.
-
C.
relatedLegalSystem
Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
-
D.
legalSystemWorkedIn
Indicates that a person carried out their professional legal activities within a particular legal system or jurisdiction.
-
E.
legalDoctrine
Indicates that one legal principle, rule, or theory is being applied, referenced, or relied upon as an authoritative basis for interpreting or deciding a legal issue.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54ce1788190ac000793cbdaba48 |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.