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Previously, researchers paid no attention to the creation of unambiguousmorpheme embeddings independent from the corpus, while such information playsan important role in expressing the exact meanings of words for parataxislanguages like Chinese. In this paper, after constructing the Chinese lexicaland semantic ontology based on word-formation, we propose a novel approach toimplanting the structured rational knowledge into distributed representation atmorpheme level, naturally avoiding heavy disambiguation in the corpus. Wedesign a template to create the instances as pseudo-sentences merely from thepieces of knowledge of morphemes built in the lexicon. To exploit hierarchicalinformation and tackle the data sparseness problem, the instance proliferationtechnique is applied based on similarity to expand the collection ofpseudo-sentences. The distributed representation for morphemes can then betrained on these pseudo-sentences using word2vec. For evaluation, we validatethe paradigmatic and syntagmatic relations of morpheme embeddings, and applythe obtained embeddings to word similarity measurement, achieving significantimprovements over the classical models by more than 5 Spearman scores or 8percentage points, which shows very promising prospects for adoption of the newsource of knowledge.

Implanting Rational Knowledge into Distributed Representation at Morpheme Level