Triple
T7150607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | density functional theory |
E166680
|
entity |
| Predicate | usesApproximationType |
P4447
|
FINISHED |
| Object | local density approximation |
—
|
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: local density approximation | Statement: [density functional theory, usesApproximationType, local density approximation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesApproximationType Context triple: [density functional theory, usesApproximationType, local density approximation]
-
A.
approximationType
chosen
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
B.
usedFromApprox
Indicates that something has been used starting from an approximate point in time or condition, rather than from a precisely defined one.
-
C.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
D.
approximationFamily
Indicates a relationship where one entity serves as an approximation or approximate representation of another within a defined family or set of approximations.
-
E.
hasApproximateShape
Indicates that one entity has a shape that is similar to, but not exactly the same as, the shape of 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_69c68886779c8190a8e3fbabffe68253 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7f28b188190b1732ca711666531 |
completed | March 27, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69c6e1caf4e48190b47bb398a3c1554d |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:46 p.m.