Triple
T11311048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Problem Solver |
E267834
|
entity |
| Predicate | aimedToModel |
P41880
|
FINISHED |
| Object | human problem solving |
—
|
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: human problem solving | Statement: [General Problem Solver, aimedToModel, human problem solving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimedToModel Context triple: [General Problem Solver, aimedToModel, human problem solving]
-
A.
usedToModel
Indicates that one entity serves as a model or representation for another entity, typically for purposes of analysis, simulation, or understanding.
-
B.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
C.
possibleModel
chosen
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
D.
aimedAtBy
Indicates that one entity serves as the target or goal toward which another entity directs an action, intention, or focus.
-
E.
adoptedModel
Indicates that one entity has formally chosen, accepted, or implemented another entity as its preferred model or standard.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787aa31888190860eecaa80da5b20 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.