Triple
T3340694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Censura Forensis |
E70251
|
entity |
| Predicate | legalSystemAnalyzed |
P25070
|
FINISHED |
| Object | civil 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: civil law | Statement: [Censura Forensis, legalSystemAnalyzed, civil law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalSystemAnalyzed Context triple: [Censura Forensis, legalSystemAnalyzed, civil law]
-
A.
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.
-
B.
legalSystemFeature
chosen
Indicates a characteristic, rule, or structural element that forms part of a particular legal system.
-
C.
legalSystemWorkedIn
Indicates that a person carried out their professional legal activities within a particular legal system or jurisdiction.
-
D.
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.
-
E.
legalSystemWorkedOn
Indicates that a legal system has been applied to, influenced, or modified by some agent or process.
- 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1c0ae44819091c851569eaf4565 |
completed | March 8, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69ada42c2ba8819091136805ce17b39d |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.