Triple
T6519763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Committee on Subsidies and Countervailing Measures |
E148350
|
entity |
| Predicate | concernsPolicyArea |
P7262
|
FINISHED |
| Object | subsidies |
—
|
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: subsidies | Statement: [Committee on Subsidies and Countervailing Measures, concernsPolicyArea, subsidies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concernsPolicyArea Context triple: [Committee on Subsidies and Countervailing Measures, concernsPolicyArea, subsidies]
-
A.
commonPolicyArea
Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
-
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.
isPartOfPolicyArea
Indicates that one policy, topic, or issue belongs to, falls under, or is categorized within a broader policy area or domain.
-
E.
policyAreaScope
Indicates the specific policy domain or thematic area to which an action, decision, or measure is relevant or applies.
- 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_69c687e68e748190baceb9298f32d3ed |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ac11d0e481908103c4b51de9521e |
completed | March 27, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69c68abbc7148190a8270d47fe10cc31 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:45 p.m.