Improving a Neural-based Tagger for Multiword Expressions Identification
Code (0)
등록된 구현이 없습니다.
Tasks
Dependency ParsingMachine TranslationSimilar Papers 제목 키워드 기반
Identification of Ambiguous Multiword Expressions Using Sequence Models and Lexical Resources
We present a simple and efficient tagger capable of identifying highly ambiguous multiword expressions (MWEs) in French texts. It is based on conditional random fields (CRF), using local context information as features. …
Identification of Multiword Expressions for Latvian and Lithuanian: Hybrid Approach
We discuss an experiment on automatic identification of bi-gram multi-word expressions in parallel Latvian and Lithuanian corpora. Raw corpora, lexical association measures (LAMs) and supervised machine learning (ML) are…
BIG-bench Machine LearningPOSThe ATILF-LLF System for Parseme Shared Task: a Transition-based Verbal Multiword Expression Tagger
We describe the ATILF-LLF system built for the MWE 2017 Shared Task on automatic identification of verbal multiword expressions. We participated in the closed track only, for all the 18 available languages. Our system is…
Feature EngineeringLexical AnalysisVeyn at PARSEME Shared Task 2018: Recurrent Neural Networks for VMWE Identification
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 TranslationTAGWord EmbeddingsThe Romanian Corpus Annotated with Verbal Multiword Expressions
This paper reports on the Romanian journalistic corpus annotated with verbal multiword expressions following the PARSEME guidelines. The corpus is sentence split, tokenized, part-of-speech tagged, lemmatized, syntactical…
DiversitySentence