# Challenges in Expanding Portuguese Resources: A View from Open Information Extraction

arXiv: https://arxiv.org/abs/2501.11851 · HTML: https://mlsanity.com/paper/2501.11851/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 30 references that are in the map.
- First posted on arXiv 21 Jan 2025.

## Builds on (most cited first, 7 of 7)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection](https://mlsanity.com/paper/2004.10643/) (2020)
- [Portuguese Named Entity Recognition using BERT-CRF](https://mlsanity.com/paper/1909.10649/) (2019)
- [Neural Open Information Extraction](https://mlsanity.com/paper/1805.04270/) (2018)
- [What the [MASK]? Making Sense of Language-Specific BERT Models](https://mlsanity.com/paper/2003.02912/) (2020)
- [WiRe57 : A Fine-Grained Benchmark for Open Information Extraction](https://mlsanity.com/paper/1809.08962/) (2018)
- [Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction](https://mlsanity.com/paper/1904.12535/) (2019)

## Abstract (arXiv)

Open Information Extraction (Open IE) is the task of extracting structured information from textual documents, independent of domain. While traditional Open IE methods were based on unsupervised approaches, recently, with the emergence of robust annotated datasets, new data-based approaches have been developed to achieve better results. These innovations, however, have focused mainly on the English language due to a lack of datasets and the difficulty of constructing such resources for other languages. In this work, we present a high-quality manually annotated corpus for Open Information Extraction in the Portuguese language, based on a rigorous methodology grounded in established semantic theories. We discuss the challenges encountered in the annotation process, propose a set of structural and contextual annotation rules, and validate our corpus by evaluating the performance of state-of-the-art Open IE systems. Our resource addresses the lack of datasets for Open IE in Portuguese and can support the development and evaluation of new methods and systems in this area.