TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Dependency Parsing	Universal Dependencies	TurkuNLP	LAS	73.28	# 5
Dependency Parsing	Universal Dependencies	TurkuNLP	UAS	60.99	# 5
Dependency Parsing	Universal Dependencies	TurkuNLP	BLEX	66.09	# 1

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Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task

CONLL 2018 · Jenna Kanerva, Filip Ginter, Niko Miekka, Akseli Leino, Tapio Salakoski ·

In this paper we describe the TurkuNLP entry at the CoNLL 2018 Shared Task on Multilingual Parsing from Raw Text to Universal Dependencies. Compared to the last year, this year the shared task includes two new main metrics to measure the morphological tagging and lemmatization accuracies in addition to syntactic trees. Basing our motivation into these new metrics, we developed an end-to-end parsing pipeline especially focusing on developing a novel and state-of-the-art component for lemmatization. Our system reached the highest aggregate ranking on three main metrics out of 26 teams by achieving 1st place on metric involving lemmatization, and 2nd on both morphological tagging and parsing.

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