Triple
T25498780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAPTA |
E639049
|
entity |
| Predicate | preferentialTreatment |
P26204
|
FINISHED |
| Object | tariff concessions |
—
|
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: tariff concessions | Statement: [SAPTA, preferentialTreatment, tariff concessions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preferentialTreatment Context triple: [SAPTA, preferentialTreatment, tariff concessions]
-
A.
priorityBenefit
Indicates that one benefit takes precedence over or is considered more important than another in a given context.
-
B.
exclusiveBenefit
Indicates that a benefit is provided to one party or group in a way that excludes others from receiving the same advantage.
-
C.
preferredConditions
Indicates the specific circumstances or environmental factors that an entity favors or finds most suitable compared to alternatives.
-
D.
typeOfTariffPreference
chosen
Indicates the specific category or kind of tariff preference applied within a trade or customs context.
-
E.
favored
Indicates that one entity is preferred, supported, or given advantage over others by another entity.
- 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_69e75dbbd2a88190b70e1e645de14b9a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f7ac2b348190af2178eed0f0f18b |
completed | May 2, 2026, 1:10 p.m. |
| PD | Predicate disambiguation | batch_69f468421ba08190880eac99135e5970 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 2:41 p.m.