Hunter Heidenreich


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Latent semantic network induction in the context of linked example senses
Hunter Heidenreich | Jake Williams
Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019)

The Princeton WordNet is a powerful tool for studying language and developing natural language processing algorithms. With significant work developing it further, one line considers its extension through aligning its expert-annotated structure with other lexical resources. In contrast, this work explores a completely data-driven approach to network construction, forming a wordnet using the entirety of the open-source, noisy, user-annotated dictionary, Wiktionary. Comparing baselines to WordNet, we find compelling evidence that our network induction process constructs a network with useful semantic structure. With thousands of semantically-linked examples that demonstrate sense usage from basic lemmas to multiword expressions (MWEs), we believe this work motivates future research.