Triple
T33711088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tariff of 1833 |
E863740
|
entity |
| Predicate | timeHorizonOfReductions |
P110188
|
FINISHED |
| Object | approximately ten years |
—
|
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: approximately ten years | Statement: [Tariff of 1833, timeHorizonOfReductions, approximately ten years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeHorizonOfReductions Context triple: [Tariff of 1833, timeHorizonOfReductions, approximately ten years]
-
A.
timeHorizonCovered
chosen
Indicates the span or duration of time that is encompassed or addressed by something (such as a plan, forecast, or agreement).
-
B.
targetReduction
Indicates a relationship where one entity is intended or expected to decrease, diminish, or lessen another entity by a specified amount or proportion.
-
C.
timeHorizonOfImpact
Indicates the span of time over which an action, event, or factor is expected to produce its effects or consequences.
-
D.
timePeriodOfRefinement
Indicates the specific time span during which a refinement or improvement of something takes place.
-
E.
timeHorizonOfLoans
Indicates the length of time over which loans are scheduled to be outstanding or repaid.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fabac0a08190aae0129f93f0b23e |
completed | May 3, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:43 a.m.