Intuitive Contrasting Map for Antonym Embeddings
This paper shows that, modern word embeddings contain information that distinguishes synonyms and antonyms despite small cosine similarities between corresponding vectors. This information is encoded in the geometry of the embeddings and could be extracted with a straight-forward and intuitive manifold learning procedure or a contrasting map. Such a map is trained on a small labeled subset of the data and can produce new embeddings that explicitly highlight specific semantic attributes of the word. The new embeddings produced by the map are shown to improve the performance on downstream tasks.
Code (1)
Tasks
Word EmbeddingsSimilar Papers 제목 키워드 기반
Antonym-Synonym Classification Based on New Sub-space Embeddings
Distinguishing antonyms from synonyms is a key challenge for many NLP applications focused on the lexical-semantic relation extraction. Existing solutions relying on large-scale corpora yield low performance because of h…
ClassificationGeneral ClassificationRelation ExtractionAntonymy-Synonymy Discrimination through the Repelling Parasiamese Neural Network
Antonymic and synonymic pairs may both occur nearby in word embeddings spaces because they have similar distributional information. Different methods have been used in order to distinguish antonyms from synonyms, making …
Word EmbeddingsA visual observation on the geometry of UMAP projections of the difference vectors of antonym and synonym word pair embeddings
Antonyms, or opposites, are sometimes defined as \emph{word pairs that have all of the same contextually relevant properties but one}. Seeing how transformer models seem to encode concepts as directions, this begs the qu…
Effect of Text Color on Word Embeddings
In natural scenes and documents, we can find the correlation between a text and its color. For instance, the word, "hot", is often printed in red, while "cold" is often in blue. This correlation can be thought of as a fe…
Word EmbeddingsCombining Discourse Markers and Cross-lingual Embeddings for Synonym--Antonym Classification
It is well-known that distributional semantic approaches have difficulty in distinguishing between synonyms and antonyms (Grefenstette, 1992; Pad{\'o} and Lapata, 2003). Recent work has shown that supervision available i…
Cross-Lingual Word EmbeddingsGeneral ClassificationWord Embeddings