Disambiguated Distributional Semantic-based Sense Inventories are hybrid knowledge bases that combines the contextual information of distributional models with the conciseness and precision of manually constructed lexical networks. In contrast to dense vector representations, our resource is human readable and interpretable (Table 1), and can be easily embedded within the Semantic Web ecosystem. Manual evaluation based on human judgments indicates the high quality of the resource, as well as the benefits of enriching top-down lexical knowledge resources with bottom-up distributional information from text.
Our approach consists of three main phases (Figure 1):
Table 1: Examples of entries for "mouse:NN" and "keyboard:NN". Trailing numbers indicate sense identifiers. Similarity and context clue scores are not shown for brevity.
Figure 1: Overview of our method for constructing a hybrid aligned resource.