Triple
T4074569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weekly Economic Report |
E86730
|
entity |
| Predicate | hasSectorFocus |
P52507
|
FINISHED |
| Object | macroeconomic 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: macroeconomic policy | Statement: [Weekly Economic Report, hasSectorFocus, macroeconomic policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectorFocus Context triple: [Weekly Economic Report, hasSectorFocus, macroeconomic policy]
-
A.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
-
B.
targetsSector
chosen
Indicates that an entity is directed toward, focused on, or intended to affect a particular economic or industry sector.
-
C.
hasEconomicFocus
Indicates that an entity is primarily concerned with, oriented toward, or specializing in economic matters, activities, or impacts.
-
D.
branchOfServiceFocus
Indicates that one entity is the primary military or organizational branch of service emphasized, specialized in, or targeted by another entity or activity.
-
E.
hasProgrammingFocus
Indicates that something is centered on, specialized in, or primarily concerned with programming.
- 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_69aed93ebe448190a1f1686e28740ac9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc245d888190ae773f9c3077953b |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.