IXA pipeline: Efficient and Ready to Use Multilingual NLP tools
By Rodrigo Agerri, Josu Bermudez, German Rigau. 2014
138 citations recorded by the source corpus.
IXA pipeline is a modular set of Natural Language Processing tools (or pipes) which provide easy access to NLP technology. It offers robust and efficient linguistic annotation to both researchers and non-NLP experts with the aim of lowering the barriers of using NLP technology either for research purposes or for small industrial developers and SMEs. IXA pipeline can be used “as is” or exploit its modularity to pick and change different components. Given its open-source nature, it can also be modified and extended for it to work with other languages. This paper describes the general data-centric architecture of IXA pipeline and presents competitive results in several NLP annotations for English and Spanish.
Subfields: Artificial Intelligence, Molecular Biology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Kawin Ethayarajh
- John Wieting
- Claire Cardie
- Kevin Gimpel
- Rada Mihalcea
- Graham Neubig
- Carmen Banea
- Daniel Matthew Cer
In Molecular Biology
- Daniel Matthew Cer
- Marc-André Zöller
- Cristina España-Bonet
- Iñigo Lopez-Gazpio
- Rada Mihalcea
- Mona T. Diab
- Eneko Agirre
- Claire Cardie
Citations in the corpus
- Survey on Automated Machine Learning (2019, background): “Regarding classical machine learning, this topic was tackled for various specific problems like natural language processing, e.g., (Agerri et al., 2014).”
- SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability (2015, methodology): “Additionally, this step collected chunk regions coming either from gold standard or from the chunking done by ixa-pipes-chunk (Agerri et al., 2014).”
- An Empirical Analysis of NMT-Derived Interlingual Embeddings and Their Use in Parallel Sentence Identification (2017, methodology): “A second system called S1-l is trained on lemmatised sentences using the MADAMIRA lemmatiser for Arabic, and the IXA pipeline (Agerri et al., 2014) for English and Spanish.”
- Hate Speech Dataset from a White Supremacy Forum (2018, background): “The resulting posts were segmented into sentences with ixa-pipes (Agerri et al., 2014).”