Porttinari-base (Duran et al., 2023) is the journalistic portion of Porttinari (which stands for “PORTuguese Treebank”), which shall be a large multigenre treebank for Portuguese (Pardo et al., 2021), following the "Universal Dependencies" international grammar framework (de Marneffe et al., 2021...
The CRPC Discourse Bank is labeled for discourse relations (also referred to as rhetorical relations or coher- ence relations), such as cause and condition, that hold between two spans of text and contribute to ensure the overall cohesion and coherence of the text. The scheme follows the principl...
The LX-WordSim-353 was created from WordSim-353 (Agirre et al., 2009). As the name suggests, this data set contains 353 pairs of words. Both words in each pair can have different morphosyntactic categories. The data set is made of nouns, adjectives, verbs and named entities, and has no multiwords...
The LX-ESSLLI 2008 data set was created from the ESSLLI 2008 Distributional Semantic Workshop shared-task set, made of 44 concrete nouns grouped in 6 semantic categories (4 animate and 2 inanimate). The grouping is done in an hierarchical way following the top 10 properties from the McRae (2005) ...
A collection of language resources for the evaluation of distributional semantic models of Portuguese: LX-SimLex-999: http://metashare.metanet4u.eu/go2/lx-simlex-999 LX-Rare Word Similarity Data set: http://metashare.metanet4u.eu/go2/lx-rare-word-similarity-dataset LX-WordSim-353: h...
The LX-Battig was created from Battig test.set (Baroni et al., 2010). This data set has 83 concrete concepts of the following 10 categories: mammals, birds, fish, vegetables, fruit, trees, vehicles, clothes, tools and kitchenware. The categories names and the concepts were translated by two trans...
LX-AP was created from the translation of Almuhareb-Poesio (ap) benchmark (Almuhareb and Poesio, 2005). The original data set was created considering three aspects: POS, frequency and ambiguity. It contains 402 names from 21 categories of WordNet, with 13 to 21 names from each one of those categ...
The test set described in was used as the basis for the assessment of word embeddings. An example entry in this data set would read: ‘Berlin Germany Lisbon Portugal’. With these four words relations – as in this example – one can test semantic analogies by using any of the possible combinations o...
The test set described in was used as the basis for the assessment of word embeddings. An example entry in this data set would read: ‘Berlin Germany Lisbon Portugal’. With these four words relations – as in this example – one can test semantic analogies by using any of the possible combinations o...
The Brands.Br corpus was built from a fraction of B2W-Reviews01 corpus. We use a set of 252 samples selected by B2W to be enriched. In Brands.Br corpus we want to solve two main challenges in product reviews corpus. The first: it is very common to find customer reviews referring to distinct thing...