| LexVec, word co-occurrence, and ConceptNet data combined using maximum entropy classifier | 0.72 | UWB at SemEval-2018 Task 10: Capturing Discriminative Attributes from Word Distributions | - |
| Gradient boosting with co-occurrence count features and JoBimText features | 0.73 | BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes | - |
| Use of Wikipedia and ConceptNet Transp. (No expl.) | 0.69 | ELiRF-UPV at SemEval-2018 Task 10: Capturing Discriminative Attributes with Knowledge Graphs and Wikipedia | - |
| SVM with ConceptNet, Wikipedia articles and WordNet synonyms | 0.74 | Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge | |
| Composes explicit vector spaces from WordNet Definitions, ConceptNet and Visual Genome | 0.69 | Identifying and Explaining Discriminative Attributes | |