Triple
T19919055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hino Nacional Brasileiro |
E478739
|
entity |
| Predicate | hasLegalRegulation |
P34675
|
FINISHED |
| Object | Brazilian federal 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: Brazilian federal law | Statement: [Hino Nacional Brasileiro, hasLegalRegulation, Brazilian federal law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalRegulation Context triple: [Hino Nacional Brasileiro, hasLegalRegulation, Brazilian federal law]
-
A.
hasRegulations
chosen
Indicates that one entity imposes, contains, or is associated with rules or regulatory requirements that govern the behavior or operation of another entity.
-
B.
supportsRegulation
Indicates that one entity endorses, backs, or advocates for the implementation or continuation of a specific regulation.
-
C.
hasRegulatedBy
Indicates that one entity is subject to control, governance, or rules imposed by another entity.
-
D.
legality
Indicates that an action, object, or situation conforms to, violates, or is evaluated in terms of formal laws or legal rules.
-
E.
hasLegalDefinitionIn
Indicates that something possesses an official legal definition within a specified legal source, system, or jurisdiction.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c3d990819089386d9f30323e8c |
completed | April 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.