Search Results for author:
Found 10 papers, 5 papers with code
TEI2GO: A Multilingual Approach for Fast Temporal Expression Identification
This corpus comprises a total of $138, 069$ documents (over six languages) with $1, 050, 921$ temporal expressions, the largest open-source annotated dataset for temporal expression identification to date.
Indexing Portuguese NLP Resources with PT-Pump-Up
Access to this data is commonly not a trivial process due to resource dispersion and the need to maintain these infrastructures online and up-to-date.
Physio: An LLM-Based Physiotherapy Advisor
The capabilities of the most recent language models have increased the interest in integrating them into real-world applications.
GPT Struct Me: Probing GPT Models on Narrative Entity Extraction
By studying the strengths and limitations of these models in the context of information extraction, we offer insights that can guide future improvements and avenues to explore in this field.
A Biomedical Entity Extraction Pipeline for Oncology Health Records in Portuguese
In this paper, we present the approach we developed to extract procedures, drugs, and diseases from oncology health records written in European Portuguese.
tieval: An Evaluation Framework for Temporal Information Extraction Systems
All in all, these problems have limited the fair comparison between approaches and consequently, the development of temporal extraction systems.
Improving Portuguese Semantic Role Labeling with Transformers and Transfer Learning
The Natural Language Processing task of determining "Who did what to whom" is called Semantic Role Labeling.
ECIR 2020 Workshops: Assessing the Impact of Going Online
In this report, we describe the experience of organizing the ECIR 2020 Workshops in this scenario from two perspectives: the workshop organizers and the workshop participants.
Mind the Gap: A Well Log Data Analysis
The main task in oil and gas exploration is to gain an understanding of the distribution and nature of rocks and fluids in the subsurface.
PAMPO: using pattern matching and pos-tagging for effective Named Entities recognition in Portuguese
This paper deals with the entity extraction task (named entity recognition) of a text mining process that aims at unveiling non-trivial semantic structures, such as relationships and interaction between entities or communities.
