Triple
T22991219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of Aparecida Day |
E572052
|
entity |
| Predicate | demographicParticipation |
P58038
|
FINISHED |
| Object | observed by many Brazilian Catholics |
—
|
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: observed by many Brazilian Catholics | Statement: [Our Lady of Aparecida Day, demographicParticipation, observed by many Brazilian Catholics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographicParticipation Context triple: [Our Lady of Aparecida Day, demographicParticipation, observed by many Brazilian Catholics]
-
A.
involvesDemographic
chosen
Indicates that an action, event, or entity is related to, affects, or includes a specific demographic group or population segment.
-
B.
hasDemographic
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
C.
demographics
Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
-
D.
demographicsIn
Indicates that demographic information is associated with or applies within a specified geographic or organizational area.
-
E.
demographicBasis
Indicates that something is determined, classified, or justified based on demographic characteristics such as age, gender, ethnicity, or similar population attributes.
- 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182eefd688190853977421540b2ce |
completed | April 29, 2026, 4:02 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:50 p.m.