ERMI at PARSEME Shared Task 2020: Embedding-Rich Multiword Expression Identification

2020-12-01 · COLING (MWE) 2020 12 · Zeynep Yirmibeşoğlu, Tunga Güngör

This paper describes the ERMI system submitted to the closed track of the PARSEME shared task 2020 on automatic identification of verbal multiword expressions (VMWEs). ERMI is an embedding-rich bidirectional LSTM-CRF model, which takes into account the embeddings of the word, its POS tag, dependency relation, and its head word. The results are reported for 14 languages, where the system is ranked 1st in the general cross-lingual ranking of the closed track systems, according to the Unseen MWE-based F1.

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Mumpitz at PARSEME Shared Task 2018: A Bidirectional LSTM for the Identification of Verbal Multiword Expressions

2018-08-01 · COLING 2018 8 · Rafael Ehren, Timm Lichte, Younes Samih

In this paper, we describe Mumpitz, the system we submitted to the PARSEME Shared task on automatic identification of verbal multiword expressions (VMWEs). Mumpitz consists of a Bidirectional Recurrent Neural Network (BR…

Machine Translation Sentence Word Embeddings

TRAVIS at PARSEME Shared Task 2020: How good is (m)BERT at seeing the unseen?

2020-12-01 · COLING (MWE) 2020 12 · Murathan Kurfali

This paper describes the TRAVIS system built for the PARSEME Shared Task 2020 on semi-supervised identification of verbal multiword expressions. TRAVIS is a fully feature-independent model, relying only on the contextual…

Veyn at PARSEME Shared Task 2018: Recurrent Neural Networks for VMWE Identification

2018-08-01 · COLING 2018 8 · Nicolas Zampieri, Manon Scholivet, Carlos Ramisch, Benoit Favre

This paper describes the Veyn system, submitted to the closed track of the PARSEME Shared Task 2018 on automatic identification of verbal multiword expressions (VMWEs). Veyn is based on a sequence tagger using recurrent …

Machine Translation TAG Word Embeddings

MultiVitaminBooster at PARSEME Shared Task 2020: Combining Window- and Dependency-Based Features with Multilingual Contextualised Word Embeddings for VMWE Detection

2020-12-01 · COLING (MWE) 2020 12 · Sebastian Gombert, Sabine Bartsch

In this paper, we present MultiVitaminBooster, a system implemented for the PARSEME shared task on semi-supervised identification of verbal multiword expressions - edition 1.2. For our approach, we interpret detecting ve…

Language Modeling Language Modelling token-classification Token Classification+1

SHOMA at Parseme Shared Task on Automatic Identification of VMWEs: Neural Multiword Expression Tagging with High Generalisation

2018-09-09 · Shiva Taslimipoor, Omid Rohanian

This paper presents a language-independent deep learning architecture adapted to the task of multiword expression (MWE) identification. We employ a neural architecture comprising of convolutional and recurrent layers wit…

Word Embeddings