Triple
T1590962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Committee (Economic and Financial) |
E34176
|
entity |
| Predicate | handlesIssue |
P3847
|
FINISHED |
| Object | macroeconomic policy questions |
—
|
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: macroeconomic policy questions | Statement: [Second Committee (Economic and Financial), handlesIssue, macroeconomic policy questions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: handlesIssue Context triple: [Second Committee (Economic and Financial), handlesIssue, macroeconomic policy questions]
-
A.
hasTargetIssue
Indicates that an entity is associated with or directed toward a specific issue, problem, or concern as its focus.
-
B.
raisesIssue
Indicates that one entity brings up, reports, or formally submits a concern, problem, or topic for attention to another entity or system.
-
C.
worksOnIssue
Indicates that an entity (typically a person or team) is actively engaged in addressing, resolving, or contributing work toward a specific issue.
-
D.
addressesIssue
chosen
Indicates that one entity deals with, responds to, or attempts to resolve a specific issue associated with another entity.
-
E.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
- 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93aedd45c819085843ac843d640e8 |
completed | March 5, 2026, 8:12 a.m. |
| PD | Predicate disambiguation | batch_69a907bdc19081908c84c5c0aa09e282 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.