Triple
T21531950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maracanazo |
E531250
|
entity |
| Predicate | impactOnBrazil |
P50618
|
FINISHED |
| Object | national trauma |
—
|
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: national trauma | Statement: [Maracanazo, impactOnBrazil, national trauma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnBrazil Context triple: [Maracanazo, impactOnBrazil, national trauma]
-
A.
impactOnTrade
Indicates a relationship where one entity causes or contributes to a change in the trade activities, volume, or conditions affecting another entity.
-
B.
nationalImpact
chosen
Indicates that something has a significant effect or influence at the level of an entire nation.
-
C.
impactOnIran
Indicates the effect or consequences that an action, event, or policy has on Iran.
-
D.
indirectImpactOn
Indicates that one entity affects another entity’s state, condition, or outcome through one or more intermediate factors rather than through a direct interaction.
-
E.
impactOnSubject
Indicates the effect, influence, or consequence that one entity, event, or action has on a specified subject.
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0a0e7c8190bbb7ed5c4dfe33af |
completed | April 26, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:27 p.m.