Triple
T25726191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaussian |
E645120
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | computational chemistry software |
C42602
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: computational chemistry software Context triple: [Gaussian, instanceOf, computational chemistry software]
-
A.
molecular modelling software
chosen
Molecular modelling software is a computational tool that simulates and visualizes the structure, properties, and interactions of molecules to support tasks such as drug design, materials development, and molecular analysis.
-
B.
cheminformatics software
Cheminformatics software is a class of computational tools designed to store, analyze, visualize, and predict chemical structures and properties using algorithms and molecular data.
-
C.
high-performance computing software
High-performance computing software consists of specialized programs and frameworks designed to efficiently execute large-scale, compute-intensive tasks by exploiting parallelism and advanced hardware architectures such as clusters, supercomputers, and GPUs.
-
D.
molecular quantum mechanics method
A molecular quantum mechanics method is a theoretical and computational approach that applies quantum mechanical principles to describe and predict the electronic structure, properties, and behavior of molecules.
-
E.
materials informatics software
Materials informatics software is a computational platform that integrates materials data, machine learning, and simulation tools to accelerate the discovery, design, and optimization of materials and their properties.
- F. None of above.
Provenance (1 batch)
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. |
Created at: April 21, 2026, 11:04 p.m.