Triple
T30801505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penal Code (1810) |
E784380
|
entity |
| Predicate | legalPrincipleEmphasized |
P61937
|
FINISHED |
| Object | legality of offences and penalties |
—
|
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: legality of offences and penalties | Statement: [Penal Code (1810), legalPrincipleEmphasized, legality of offences and penalties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalPrincipleEmphasized Context triple: [Penal Code (1810), legalPrincipleEmphasized, legality of offences and penalties]
-
A.
legalConcept
Indicates a relationship where something is classified or treated as a concept defined and governed by law or legal theory.
-
B.
principleClarified
Indicates that a principle has been made clearer or more explicit, typically by explanation, refinement, or elaboration.
-
C.
hasLegalPrincipleInvoked
Indicates that a legal case, action, or decision relies on, cites, or is based upon a specific legal principle.
-
D.
legalBasis
Indicates the legal rule, authority, or justification under which an action, decision, or status is established or carried out.
-
E.
lawCharacteristicInText
chosen
Indicates that a specific legal characteristic or feature is expressed, described, or referenced within a given text.
- 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_69f224b3a7ec819096939414d103e31e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe610e1f6881908f10070ba64643cf |
completed | May 8, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69fe604c6c008190ad659e9b9fa82f7b |
completed | May 8, 2026, 10:14 p.m. |
Created at: April 29, 2026, 8:42 p.m.