Entity Insertion in Wikipedia
Multilingual entity insertion in Wikipedia articles
Proposes a framework for inserting entities into Wikipedia articles across multiple languages. It processes Wikipedia dumps to extract data and train models for entity insertion. The key components are: 1) Data processing pipeline to extract relevant data from Wikipedia dumps. 2) Modeling code for training entity insertion models using a ranking loss or pointwise loss. 3) Benchmarking code to evaluate models against baselines like BM25, EntQA, and GPT language models.
Machine LearningNatural Language
- Technical
- Source code: Lab Github
- Last commit: 2024-10-04
Our research aims to make sense of large amounts of data. Frequently, the data we analyze is collected on the Web, e.g., using server logs, social media, wikis, online news, online games, etc. We distill heaps of raw data into meaningful insights by developing and applying algorithms and techniques in areas including social and information network analysis, machine learning, computational social science, data mining, natural language processing, and human computation.
This page was last edited on 2024-04-16.
This page was last edited on 2024-04-16.