my personal homepage and blog

"Bootstrapping Relationship Extractors with Distributional Semantics" (Batista et al., 2015) in EMNLP'15 - Python implementation

Different retrieval techniques implemented in Haystack - presented at PyCon Lithuania 2025 🇱🇹

A plug-in to generate various evaluation metrics and reports ( PR-curves, classifications reports, confusion matrix) for supervised machine learning models using only two lines of code.

Implementation with some extensions of the paper "Snowball: Extracting Relations from Large Plain-Text Collections" (Agichtein and Gravano, 2000)

An implementation of a full named-entity evaluation metrics based on SemEval'13 Task 9 - not at tag/token level but considering all the tokens that are part of the named-entity

My dot files for several things

Resources developed by and for the project REACTION (Retrieval, Extraction and Aggregation Computing Technology for Integrating and Organizing News) an initiative for developing a computational jou…

Datasets to train supervised classifiers for Named-Entity Recognition in different languages (Portuguese, German, Dutch, French, English)

Explore relações de apoio e oposição, entre personalidades políticas, expressas em títulos de notícias preservadas no arquivo.pt

A collections of public and free annotated datasets of relationships between entities/nominals (Portuguese and English)

"Convolutional Neural Networks for Sentence Classification" (Kim 2014) - https://www.aclweb.org/anthology/D14-1181

Sequence LAbeliNG with Neural Networks: "Neural Architectures for Named Entity Recognition" (Lample et al., 2016) and "End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF" (Ma, 2016)

Old projects of mine, done during high-school or university and found in old hard-drives

GermEval 2019 Task 1 - Shared Task on Hierarchical Classification of Blurbs

Assorted exercises and proof-of-concepts to understand and study machine learning and statistical learning theory

Aspect-Based Sentiment Analysis Experiments

An example on how to train supervised classifiers for multi-label text classification using sklearn pipelines

Toponym Disambiguation using Ontology-based Semantic Similarity.

Snowball: Extracting Relations from Large Plain-Text Collections

Simple webapps, relying on DBpedia as a data-source.