We present the findings of SemEval-2022 Task 11 on Multilingual Complex Named Entity
Recognition MULTICONER. Divided into 13 tracks, the task focused on methods to identify …

As a common psychological disorder, depression is generally detected based on scales and
interviews, which are often affected by subjective or environmental factors. In order to assist …

The automatic generation of reading comprehension questions, referred to as question
generation (QG), is attracting attention in the field of education. To achieve efficient …

In recent years, the deep neural network has been introduced as an effective learning
method in many natural language processing (NLP) applications. One of these applications …

In the Australian construction industry, effective supply chain risk management (SCRM) is
critical due to its complex networks and susceptibility to various risks. This study explores the …

The ubiquity of offensive content on social media is a growing cause for concern among
companies and government organizations. Recently, transformer-based models such as …

Legal documents are often long and unstructured, making them challenging and time-
consuming to apprehend. An automatic system that can identify relevant entities and labels …

Named entities (NE) are integral for preserving context and conveying accurate information
in the machine translation (MT) task. Challenges often lie in handling NE diversity …

Named‑entity recognition (NER) is a crucial task in natural language processing, espe‑cially
for extracting meaningful information from unstructured text data. In the healthcare domain …

This paper explores the automated extraction of job titles from unstructured historical job
advertisements, using a corpus of digitized German-language newspapers from 1850-1950 …