Triple
T18871689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portuguese law |
E461583
|
entity |
| Predicate | recognizesLegalProfession |
P23182
|
FINISHED |
| Object | advogado |
—
|
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: advogado | Statement: [Portuguese law, recognizesLegalProfession, advogado]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recognizesLegalProfession Context triple: [Portuguese law, recognizesLegalProfession, advogado]
-
A.
legalProfessionIncludes
Indicates that a legal profession or role encompasses, involves, or includes another specified legal function, specialization, or activity.
-
B.
legalProfessionRole
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
C.
legalProfessionTypeRegulated
Indicates that the specified type of legal profession is subject to formal regulation or oversight by an authority.
-
D.
recognizesProfession
chosen
Indicates that one entity acknowledges or identifies another entity’s professional role or occupation as such.
-
E.
hasRegulatedProfession
Indicates that an entity practices or is associated with a profession that is formally regulated by laws, standards, or licensing authorities.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c2a9dd04819083133ded30337962 |
completed | April 20, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69e48d22dde8819093b1d963bd673365 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:57 a.m.