Papers with Sememe Prediction

2 papers
How Sememic Components Can Benefit Link Prediction for Lexico-Semantic Knowledge Graphs? (2025.emnlp-main)

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Challenge: Existing methods to predict missing triples in Knowledge Graphs are limited by semantic information.
Approach: They propose a method to leverage sememe knowledge to enhance LP . LP is a technique that integrates structural and textual information into a Knowledge Graph .
Outcome: The proposed method improves LP performance in English and Chinese . it improves on WN18RR, HN7 and CWN5, respectively .
Morpheme Sense Disambiguation: A New Task Aiming for Understanding the Language at Character Level (2024.lrec-main)

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Challenge: Morphemes are a strong linguistic feature to capture lexical semantics, but lack of morpheme-informed resources and the expense of manual annotations hinder morphme-enhanced methods.
Approach: They propose a task of Morpheme Sense Disambiguation with two subtasks in-text and in-word to generalize morpheme features on more tasks.
Outcome: The proposed tasks are based on two morpheme-annotated datasets for Chinese . the best model yields a promising precision of 77.66% on in-text and 88.19% on in word .

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