Triple
T15741831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramsey–Cass–Koopmans model |
E381618
|
entity |
| Predicate | optimizationAgent |
P94144
|
FINISHED |
| Object | social planner |
—
|
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: social planner | Statement: [Ramsey–Cass–Koopmans model, optimizationAgent, social planner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: optimizationAgent Context triple: [Ramsey–Cass–Koopmans model, optimizationAgent, social planner]
-
A.
optimizationRole
chosen
Indicates the role or function an entity plays within an optimization process or strategy.
-
B.
optimizationDomain
Indicates the domain, field, or context within which an optimization process or optimization-related activity is applied.
-
C.
optimizationTarget
Indicates that one entity is the goal or objective that another entity is trying to improve, optimize, or make more efficient.
-
D.
optimizationType
Indicates the specific strategy or method used to improve performance or efficiency within a given process or system.
-
E.
optimize
Indicates improving a process, system, or outcome to achieve the best possible performance or efficiency under given constraints.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.