Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Abstract Local models for Entity Disambiguation (ED) have today become extremely
powerful, in most part thanks to the advent of large pre-trained language models. However …

Abstract Named Entity Recognition (NER) is the task of identifying named entities in texts
and classifying them through specific semantic categories, a process which is crucial for a …

A large body of research work has proposed verification techniques for rumors spreading in
social media that mainly relied on subjective evidence, eg, propagation networks or user …

Relation Extraction (RE) is a task that identifies relationships between entities in a text,
enabling the acquisition of relational facts and bridging the gap between natural language …

Named entities–typically expressed via proper nouns–play a key role in Natural Language
Processing, as their identification and comprehension are crucial in tasks such as Relation …

Idioms are phrases which present a figurative meaning that cannot be (completely) derived
by looking at the meaning of their individual components. Identifying and understanding …

The CoNLL-03 corpus is arguably the most well-known and utilized benchmark dataset for
named entity recognition (NER). However, prior works found significant numbers of …

With the advent of Large Language Models (LLMs), the potential of Retrieval Augmented
Generation (RAG) techniques have garnered considerable research attention. Numerous …

Local models have recently attained astounding performances in Entity Disambiguation
(ED), with generative and extractive formulations being the most promising research …