Triple
T21941316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of the Federal District (Brazil) |
E541826
|
entity |
| Predicate | languageOfLegalDescription |
P123322
|
FINISHED |
| Object | Portuguese |
—
|
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: Portuguese | Statement: [Flag of the Federal District (Brazil), languageOfLegalDescription, Portuguese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLegalDescription Context triple: [Flag of the Federal District (Brazil), languageOfLegalDescription, Portuguese]
-
A.
legalDesignationLanguage
chosen
Indicates the language in which a legal designation, status, or title is formally expressed or recorded.
-
B.
languageOfLegalCode
Indicates that a specified language is the language in which a particular legal code or body of law is written or officially expressed.
-
C.
languageOfJurisdiction
Indicates the language officially used for legal and administrative purposes within a given jurisdiction.
-
D.
legalCharacterization
Indicates how an action, event, or situation is classified or characterized under a specific legal framework or set of laws.
-
E.
languageOfNotation
Indicates the language in which a given notation, script, or symbolic system is expressed or encoded.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12422245c8190af128b29e2d9c1fc |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:56 p.m.