Triple
T25725958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kohn–Sham equations |
E645115
|
entity |
| Predicate | aimsToReproduce |
P114497
|
FINISHED |
| Object | exact ground-state electron density |
—
|
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: exact ground-state electron density | Statement: [Kohn–Sham equations, aimsToReproduce, exact ground-state electron density]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimsToReproduce Context triple: [Kohn–Sham equations, aimsToReproduce, exact ground-state electron density]
-
A.
aimsToModel
chosen
Indicates that one entity is intended or designed to represent, simulate, or approximate the behavior, structure, or properties of another entity.
-
B.
aimOf
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
-
C.
aimsToDemonstrate
Indicates an intentional effort by one entity to show, prove, or make evident a particular idea, claim, or outcome to others.
-
D.
aimedAtBy
Indicates that one entity serves as the target or goal toward which another entity directs an action, intention, or focus.
-
E.
aimsToExplain
Indicates that one entity intends to clarify, make understandable, or provide an explanation about another entity, concept, or situation.
- 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_69e77e85254081908d79ee4e8715f283 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f600c18a14819081b5914dd3b0f9cf |
completed | May 2, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 21, 2026, 11:04 p.m.