Triple
T31600151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plano Verão |
E806327
|
entity |
| Predicate | hadSideEffect |
P39638
|
FINISHED |
| Object | distortions in relative prices |
—
|
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: distortions in relative prices | Statement: [Plano Verão, hadSideEffect, distortions in relative prices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadSideEffect Context triple: [Plano Verão, hadSideEffect, distortions in relative prices]
-
A.
possibleSideEffect
Indicates that one entity may occur as a side effect or unintended consequence of another entity or action.
-
B.
hadEffectUntil
Indicates that an effect or condition held true up to a specific time or event, after which it no longer applied.
-
C.
sideEffect
chosen
Indicates that one entity is an unintended or secondary effect resulting from the use or occurrence of another entity.
-
D.
hasSeriousSideEffect
Indicates that an entity (such as a treatment, drug, or intervention) causes or is associated with a significant or severe adverse effect on another entity (typically a patient or biological system).
-
E.
hasSecondaryEffect
Indicates that an action, event, or primary effect produces an additional, indirect, or consequential effect beyond its main intended outcome.
- 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_69f348d54ccc8190a03b5df9a2b40b25 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a837c5c8819084ab09a81c0fc2c6 |
completed | May 3, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69f6a75656e081908739ed9e2f600e42 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 10:32 p.m.