Triple
T274920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brexit |
E5225
|
entity |
| Predicate | policyAreaImpacted |
P7262
|
FINISHED |
| Object | trade policy |
—
|
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: trade policy | Statement: [Brexit, policyAreaImpacted, trade policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyAreaImpacted Context triple: [Brexit, policyAreaImpacted, trade policy]
-
A.
policyFocus
Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
-
B.
coversPolicyArea
Indicates that a policy, document, or initiative includes or addresses a particular policy area or topic within its scope.
-
C.
hasPolicyArea
chosen
Indicates that an entity (such as a policy, program, or initiative) is associated with or pertains to a specific policy area or domain.
-
D.
policyDomain
Indicates the thematic or subject-matter area to which a given policy, rule, or regulatory action belongs.
-
E.
governmentInvolvement
Indicates that a government participates in, influences, regulates, or otherwise plays a role in the specified activity, process, or 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dd1cdf881909c2c9b77b7f88684 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7345c4819086c21710864a1b42 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.