Papers by Pedro Javier Ortiz Suárez
Establishing a New State-of-the-Art for French Named Entity Recognition (2020.lrec-1)
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| Challenge: | Named entity recognition (NER) is a task consisting in identifying text spans that denote named entities such as person, location and organization names. |
| Approach: | They manually annotated the French TreeBank with information related to named entities . they sketch the underlying annotation guidelines and provide a few figures about the annotations . |
| Outcome: | The French TreeBank is the main source of morphosyntactic and syntactical annotations for French. |
Building a User-Generated Content North-African Arabizi Treebank: Tackling Hell (2020.acl-main)
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Djamé Seddah, Farah Essaidi, Amal Fethi, Matthieu Futeral, Benjamin Muller, Pedro Javier Ortiz Suárez, Benoît Sagot, Abhishek Srivastava
| Challenge: | a treebank for a north-African Arabic dialect known for code-switching is made freely available . authors: geopolitical events are a factor highlighting a language deficiency in terms of natural language processing resources . |
| Approach: | They propose to make a treebank for a romanized user-generated content variety of Algerian . they supplement it with 50k unlabeled sentences from common crawl and web-crawled data . |
| Outcome: | The proposed treebank is made of 1500 sentences, fully annotated in morpho-syntax and universal dependency syntax, with full translation at both the word and sentence levels. |
CamemBERT: a Tasty French Language Model (2020.acl-main)
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Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric de la Clergerie, Djamé Seddah, Benoît Sagot
| Challenge: | Pretrained language models are now ubiquitous in Natural Language Processing, but their use in other languages is limited. |
| Approach: | They propose to train monolingual Transformer-based model for other languages using web crawled data instead of Wikipedia data and a relatively small web crawl dataset leads to better results. |
| Outcome: | The proposed model performs as well as those obtained using larger datasets. |
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages (2020.acl-main)
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| Challenge: | a recent trend in neural NLP has been the introduction of feature-based and fine-tuning methods . we train monolingual contextualized word embeddings for five mid-resource languages . |
| Approach: | They use common Crawl corpus to train monolingual contextualized word embeddings . they compare performance of OSCAR-based and Wikipedia-based embeddables on part-of-speech tasks . |
| Outcome: | The results show that OSCAR-based and Wikipedia-based embeddings perform better than Wikipedia-style embedders on part-of-speech tagging and parsing tasks. |