Triple
T16344704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annecy Round |
E396900
|
entity |
| Predicate | numberOfTariffConcessions |
P123052
|
FINISHED |
| Object | 5000 |
—
|
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: 5000 | Statement: [Annecy Round, numberOfTariffConcessions, 5000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTariffConcessions Context triple: [Annecy Round, numberOfTariffConcessions, 5000]
-
A.
tariffStructure
Indicates the specific schedule, rates, and rules that define how tariffs or fees are applied within a pricing or taxation system.
-
B.
regulatesTariffs
Indicates that one entity has authority to control, set, or adjust the tariffs imposed on another entity or on certain transactions.
-
C.
averageTariffRateOnDutiableImports
Indicates the average tariff rate applied specifically to imported goods that are subject to customs duties.
-
D.
concessionCountry
Indicates that one country grants rights, privileges, or control over certain resources, land, or activities to another party through a formal concession.
-
E.
usesTariffSystem
Indicates that one entity applies or operates under a tariff-based system for pricing, taxation, or fees in its interactions or transactions.
- F. None of above. chosen
Provenance (4 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2da0da1808190b6477613a07c7a88 |
completed | April 18, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:07 a.m.