Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Zaporojets, Klim"'
Knowledge graphs constantly evolve with new entities emerging, existing definitions being revised, and entity relationships changing. These changes lead to temporal degradation in entity linking models, characterized as a decline in model performance
Externí odkaz:
http://arxiv.org/abs/2410.09127
This paper presents the first study for temporal relation extraction in a zero-shot setting focusing on biomedical text. We employ two types of prompts and five LLMs (GPT-3.5, Mixtral, Llama 2, Gemma, and PMC-LLaMA) to obtain responses about the temp
Externí odkaz:
http://arxiv.org/abs/2406.11486
Autor:
Javadi, Saeedeh, Moradan, Atefeh, Sorkhpar, Mohammad, Zaporojets, Klim, Mottin, Davide, Assent, Ira
Entity summarization aims to compute concise summaries for entities in knowledge graphs. Existing datasets and benchmarks are often limited to a few hundred entities and discard graph structure in source knowledge graphs. This limitation is particula
Externí odkaz:
http://arxiv.org/abs/2406.08435
Autor:
Bitew, Semere Kiros, Schelstraete, Vincent, Zaporojets, Klim, Van Nieuwenhove, Kimberly, Meganck, Reitske, Develder, Chris
In disentangling the heterogeneity observed in psychopathology, personality of the patients is considered crucial. While it has been demonstrated that personality traits are reflected in the language used by a patient, we hypothesize that this enable
Externí odkaz:
http://arxiv.org/abs/2311.04088
Autor:
D'Oosterlinck, Karel, Remy, François, Deleu, Johannes, Demeester, Thomas, Develder, Chris, Zaporojets, Klim, Ghodsi, Aneiss, Ellershaw, Simon, Collins, Jack, Potts, Christopher
Timely and accurate extraction of Adverse Drug Events (ADE) from biomedical literature is paramount for public safety, but involves slow and costly manual labor. We set out to improve drug safety monitoring (pharmacovigilance, PV) through the use of
Externí odkaz:
http://arxiv.org/abs/2305.13395
Autor:
Zaporojets, Klim
Artificial Intelligence (AI) has huge impact on our daily lives with applications such as voice assistants, facial recognition, chatbots, autonomously driving cars, etc. Natural Language Processing (NLP) is a cross-discipline of AI and Linguistics, d
Externí odkaz:
http://arxiv.org/abs/2304.07625
Autor:
Zaporojets, Klim, Kaffee, Lucie-Aimee, Deleu, Johannes, Demeester, Thomas, Develder, Chris, Augenstein, Isabelle
In our continuously evolving world, entities change over time and new, previously non-existing or unknown, entities appear. We study how this evolutionary scenario impacts the performance on a well established entity linking (EL) task. For that study
Externí odkaz:
http://arxiv.org/abs/2302.02500
Publikováno v:
Applied Intelligence, 1-19 (2022)
This work presents a new dialog dataset, CookDial, that facilitates research on task-oriented dialog systems with procedural knowledge understanding. The corpus contains 260 human-to-human task-oriented dialogs in which an agent, given a recipe docum
Externí odkaz:
http://arxiv.org/abs/2206.08723
We consider the task of document-level entity linking (EL), where it is important to make consistent decisions for entity mentions over the full document jointly. We aim to leverage explicit "connections" among mentions within the document itself: we
Externí odkaz:
http://arxiv.org/abs/2108.13530
We consider a joint information extraction (IE) model, solving named entity recognition, coreference resolution and relation extraction jointly over the whole document. In particular, we study how to inject information from a knowledge base (KB) in s
Externí odkaz:
http://arxiv.org/abs/2107.02286