Triple
T27132186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Convertibility Plan (Argentina) |
E681588
|
entity |
| Predicate | initialEffect |
P1634
|
FINISHED |
| Object | sharp reduction in inflation |
—
|
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: sharp reduction in inflation | Statement: [Convertibility Plan (Argentina), initialEffect, sharp reduction in inflation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialEffect Context triple: [Convertibility Plan (Argentina), initialEffect, sharp reduction in inflation]
-
A.
initialAction
Indicates the first or starting action taken in a sequence of actions or events.
-
B.
primaryEffect
chosen
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
C.
sideEffect
Indicates that one entity is an unintended or secondary effect resulting from the use or occurrence of another entity.
-
D.
tookEffect
Indicates that a change, rule, condition, or event became active, operative, or started producing its intended consequences.
-
E.
canonicalEffect
Indicates the standard or primary effect that an action, event, or entity is typically understood to produce.
- 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_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 27, 2026, 9:05 a.m.