The experimental spectra were annotated through three strategies: experimental spectral databases matching, in silico spectral databases matching, and de novo annotation. The first one relies on the use of GNPS workflows and FBMN. The in silico annotation workflow relies on NAP and CaraMel. The manual analysis of NMR data and the application of the SIRI-US software, both employed in this study, are integral components of the third strategy. The latter allowed for the annotation of experimental spectra without depending on spectral databases, even in cases undisclosed chemical structures were involved. A new workflow was created to combine the annotations from all the GNPS workflows (i.e., FBMN, NAP), SIRIUS and the 13 C NMR annotation workflow called CaraMel. This new workflow named « CATHEDRAL » for « Combining THE DiffeRent Annotation tooLs. » is an in-house script written in Python. This script allows the assignment of a confidence level score using a custom confidence level system, determined based on the outcomes of the comparative analysis. First, FBMN and NAP results are merged to retrieve the spectral matches versus experimental spectral libraries from GNPS and Pinaceae in a silico database simulated by MetFrag. Secondly, the resulting metadata is exported as a "recap.csv" file. A PRED column is added to the table, and features are "scored" as follows: 1 for the FBMN annotated features, 2 for the features without any FBMN annotation but with at least one NAP -MetFrag candidate, and 3 for all the remaining features. The comparison process starts with the SMILES from the FBMN workflow and the MetFragSMILES from the NAP workflow. The corresponding InChIKeys are then generated via functions from the RDKit Python library. The canonical SMILES from 13 C NMR annotations structures, obtained from ChemDraw 20.1.1., and gathered into a file called «smile_nmr.txt», follow the same process as above. The resulting InChiKeys for each feature and CaraMel annotations are thus compared to the corresponding SIRIUS annotations InChiKeys.