Triple
T30409502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Padre Miguel |
E773572
|
entity |
| Predicate | hasSambaSchool |
P178821
|
FINISHED |
| Object | Mocidade Independente de Padre Miguel |
—
|
NE NERFINISHED |
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: Mocidade Independente de Padre Miguel | Statement: [Padre Miguel, hasSambaSchool, Mocidade Independente de Padre Miguel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSambaSchool Context triple: [Padre Miguel, hasSambaSchool, Mocidade Independente de Padre Miguel]
-
A.
hasSchoolIn
Indicates that a school is located within or operates in a specified place or region.
-
B.
hasSchoolOrganization
Indicates that an educational institution is associated with or contains a specific school-related organization or group.
-
C.
hasGymnasium
Indicates that one entity possesses, includes, or is equipped with a gymnasium as a facility or feature.
-
D.
hasSchoolsAccess
Indicates that one entity has permission or the ability to access schools or school-related resources associated with another entity.
-
E.
hasFictionalSchool
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
- F. None of above. chosen
Provenance (4 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_69f22490b8b48190ab10c886a8d58c89 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71421e8d08190807ccfb15d0f0ddb |
completed | May 3, 2026, 9:23 a.m. |
Created at: April 29, 2026, 8:04 p.m.