Triple
T15579443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Creating Opportunities |
E374453
|
entity |
| Predicate | opposesEconomicPolicy |
P74534
|
FINISHED |
| Object | statism |
—
|
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: statism | Statement: [Creating Opportunities, opposesEconomicPolicy, statism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposesEconomicPolicy Context triple: [Creating Opportunities, opposesEconomicPolicy, statism]
-
A.
economicPolicyOrientation
Indicates the general stance or approach an entity takes toward economic policy, such as its preferred principles, priorities, or strategies in managing the economy.
-
B.
opposesLabel
chosen
Indicates that one entity expresses disagreement with, resistance to, or active opposition against another entity or its position.
-
C.
economicPolicyType
Indicates the classification of an economic policy according to its general type or category (e.g., fiscal, monetary, trade).
-
D.
economicPolicyOutcome
Indicates the resulting economic conditions, effects, or consequences that arise from implementing a particular economic policy.
-
E.
opposedPolicyContext
Indicates that an entity opposed a specific policy within a particular situational, temporal, or institutional 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e24064c8190b132c3092877fbfa |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda817e9881909b0c66fc9056f7d5 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:11 a.m.