Triple
T23470609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green's function |
E569215
|
entity |
| Predicate | usedToSolve |
P8791
|
FINISHED |
| Object | Poisson's equation |
—
|
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: Poisson's equation | Statement: [Green's function, usedToSolve, Poisson's equation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToSolve Context triple: [Green's function, usedToSolve, Poisson's equation]
-
A.
commonlySolvedBy
chosen
Indicates that a problem, task, or issue is typically addressed or resolved through a particular method, tool, or agent.
-
B.
solved
Indicates that one entity has successfully found a solution or answer to a problem, task, or challenge involving another entity.
-
C.
providesSolutionFor
Indicates that one entity offers or supplies a remedy, answer, or resolution to a problem, need, or issue associated with another entity.
-
D.
problemTypeSolved
Indicates that a given problem has been successfully solved or resolved by a particular entity or method.
-
E.
usedToFix
Indicates that one entity serves as a tool, method, or resource employed to repair, correct, or resolve a problem or defect in another entity.
- 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a6ff8dc0819086961b1f07030d9c |
completed | April 29, 2026, 6:36 a.m. |
| PD | Predicate disambiguation | batch_69f06201d33481909b5fd7b92d03e658 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:54 p.m.