Triple
T1151920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch courts |
E23694
|
entity |
| Predicate | basedOnLegalSystem |
P14384
|
FINISHED |
| Object | civil law system |
—
|
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: civil law system | Statement: [Dutch courts, basedOnLegalSystem, civil law system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnLegalSystem Context triple: [Dutch courts, basedOnLegalSystem, civil law system]
-
A.
relatedLegalSystem
Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
-
B.
legalSystem
Indicates the formal framework of laws, rules, and institutions that governs how legal matters are defined, interpreted, and enforced within a society or jurisdiction.
-
C.
separateLegalSystem
Indicates that one entity maintains its own distinct and independent legal system from another entity.
-
D.
legalSystemWorkedOn
Indicates that a legal system has been applied to, influenced, or modified by some agent or process.
-
E.
legalOrigin
chosen
Indicates the foundational legal system or jurisdiction from which an entity’s laws, regulations, or legal framework are derived.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8d2dd8819081c779d408c2651d |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.