Papers with Japanese Wikipedia

3 papers
A New Surprise Measure for Extracting Interesting Relationships between Persons (2021.eacl-demos)

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Challenge: Interesting facts are useful information for a variety of important tasks.
Approach: They propose a method that extracts all personal relationships from dependency trees and calculates surprise scores for distributed representations of the extracted relationships in an unsupervised manner.
Outcome: The proposed method extracts all personal relationships from dependency trees for the texts and calculates surprise scores for distributed representations of the extracted relationships in an unsupervised manner.
Resource of Wikipedias in 31 Languages Categorized into Fine-Grained Named Entities (2022.coling-1)

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Challenge: a resource of Wikipedias in 31 languages is categorized into Extended Named Entity (ENE) ENE version 8 has 219 fine-grained NE categories.
Approach: They describe a resource of Wikipedias in 31 languages categorized into Extended Named Entity (ENE) they first categorized 920 K Japanese Wikipedia pages using machine learning, then shared a task of Wikipedia categorization into 30 languages .
Outcome: The proposed system is based on a dataset of Japanese Wikipedia pages . the dataset shows the best performance among the 30 languages .
JEMHopQA: Dataset for Japanese Explainable Multi-Hop Question Answering (2024.lrec-main)

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Challenge: a dataset for explainable QA in Japanese is available for many languages, but not in other languages.
Approach: They present a multi-hop QA dataset based on Japanese Wikipedia . it includes question-answer pairs and supporting evidence in the form of derivation triples . they show that the dataset is sufficiently challenging for state-of-the-art LLMs based upon this dataset .
Outcome: The proposed dataset is based on Japanese Wikipedia and can be used to evaluate QA tasks.

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