Triple
T25726392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CP2K |
E645123
|
entity |
| Predicate | usesBasisSetType |
P135136
|
FINISHED |
| Object | Gaussian basis sets |
—
|
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: Gaussian basis sets | Statement: [CP2K, usesBasisSetType, Gaussian basis sets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBasisSetType Context triple: [CP2K, usesBasisSetType, Gaussian basis sets]
-
A.
usesBasisFunctions
chosen
Indicates that one entity represents, models, or computes another entity by expressing it as a combination of specified basis functions.
-
B.
basisType
Indicates the type or category of foundational support or underlying structure on which something is based.
-
C.
hasBasisIn
Indicates that one entity is founded, derived, or justified on the grounds of another entity.
-
D.
hasStandardBasis
Indicates that a given vector space is equipped with or possesses its usual canonical set of basis vectors.
-
E.
hasAlternativeBasis
Indicates that something is supported, justified, or founded on a different underlying reason, source, or principle than the primary or original one.
- 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_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 21, 2026, 11:04 p.m.