The ADAPT Enhanced Dependency Parser at the IWPT 2020 Shared Task (2020)

Abstract: We describe the ADAPT system for the 2020 IWPT Shared Task on parsing enhanced Universal Dependencies in 17 languages. We implement a pipeline approach using UDPipe and UDPipe-future to provide initial levels of annotation. The enhanced dependency graph is either produced by a graph-based semantic dependency parser or is built from the basic tree using a small set of heuristics. Our results show that, for the majority of languages, a semantic dependency parser can be successfully applied to the task of parsing enhanced dependencies. Unfortunately, we did not ensure a connected graph as part of our pipeline approach and our competition submission relied on a last-minute fix to pass the validation script which harmed our official evaluation scores significantly. Our submission ranked eighth in the official evaluation with a macro-averaged coarse ELAS F1 of 67.23 and a treebank average of 67.49. We later implemented our own graph-connecting fix which resulted in a score of 79.53 (language average) or 79.76 (treebank average), which would have placed fourth in the competition evaluation.

## introduction the 2020 iwpt shared task on enhanced dependency parsing @xcite requires participants to predict the enhanced dependencies (deps column in the conll-u format) in addition to sentence boundaries, tokenisation, lemmata, pos tags, morphological features and the basic dependency tree. we take a pipeline approach using 1. udpipe for sentence splitting and tokenisation, 2. ensembles of udpipe-future basic parsers, that also predict lemmata, pos tags and morphological features, with added support for multi-treebank models @xcite , and 3. two types of enhancers: (a) copying the basic tree and applying a small set of heuristics (baseline system), and (b) a graph-based semantic dependency parser @xcite . to enable reproduction of our results, we make available our helper scripts and modifications of the semantic parser. 1 our approach to the task does not guarantee a connected graph -something that we did not account for. thus, on submission day, we did not have an appropriate solution ready to fix our outputs but were able to provide a valid submission due to some functionality that was added to the quick-fix tool provided by the organisers 2 to alter the enhanced graph. the solution was designed primarily to make the files pass validation but in doing so, harms f1-score. in a post-competition run, we addressed the connected graph issue with an alternative solution which increased our macroaveraged elas f1-score from 67.23 to 79.53 and the treebank average from 67.49 to 79.76. ## conclusion in this system submission, we use a graph-based semantic parser to parse enhanced dependencies and compare to a baseline in which we create enhanced graphs from the basic tree using a very limited set of heuristics. avenues for future work include: post-processing predict the head and label for edges connecting fragments (as opposed to a dummy "0:root" edge) where this information could come from new edges available from lowering the score threshold or from the basic tree.