Universal Dependencies Parsing for Colloquial Singaporean English

Singlish can be interesting to the ACL community both linguistically as a major creole based on English, and computationally for information extraction and sentiment analysis of regional social media. We investigate dependency parsing of Singlish by constructing a dependency treebank under the Universal Dependencies scheme, and then training a neural network model by integrating English syntactic knowledge into a state-of-the-art parser trained on the Singlish treebank. Results show that English knowledge can lead to 25% relative error reduction, resulting in a parser of 84.47% accuracies. To the best of our knowledge, we are the first to use neural stacking to improve cross-lingual dependency parsing on low-resource languages. We make both our annotation and parser available for further research.Comment: Accepted by ACL 201

An improved neural network model for joint POS tagging and dependency parsing

We propose a novel neural network model for joint part-of-speech (POS) tagging and dependency parsing. Our model extends the well-known BIST graph-based dependency parser (Kiperwasser and Goldberg, 2016) by incorporating a BiLSTM-based tagging component to produce automatically predicted POS tags for the parser. On the benchmark English Penn treebank, our model obtains strong UAS and LAS scores at 94.51% and 92.87%, respectively, producing 1.5+% absolute improvements to the BIST graph-based parser, and also obtaining a state-of-the-art POS tagging accuracy at 97.97%. Furthermore, experimental results on parsing 61 "big" Universal Dependencies treebanks from raw texts show that our model outperforms the baseline UDPipe (Straka and Strakov\'a, 2017) with 0.8% higher average POS tagging score and 3.6% higher average LAS score. In addition, with our model, we also obtain state-of-the-art downstream task scores for biomedical event extraction and opinion analysis applications. Our code is available together with all pre-trained models at: https://github.com/datquocnguyen/jPTDPComment: 11 pages; In Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, to appea

No Child Left Behind: Universal Child Care and Children’s Long-Run Outcomes

There is a heated debate in the US, Canada and many European countries about introducing universally accessible child care. However, studies on universal child care and child development are scarce and only consider short-run outcomes. We analyze the introduction of universal child care in Norway, addressing the impact on children's long-run outcomes. Our precise and robust difference-in-difference estimates show that child care had strong positive effects on children's educational attainment and labor market participation, and also reduced welfare dependency. Subsample analysis indicates that children with low educated mothers and girls benefit the most from child care.universal child care, child development, long-run outcomes

Reference to dependencies established in multiple-wh questions

In discourse, a universal statement establishes a dependency between sets of objects, which can support the evaluation of singular pronouns in a subsequent sentence. Two well-known phenomena involving such reference to a dependency are quantificational subordination and telescoping. This paper argues that a multiple-wh question admitting a pair-list answer can support subordination and telescoping, just like universal statements. Accordingly, the relevant phenomena are classified into two kinds of reference to dependencies, called ‘question subordination’ and ‘question telescoping’, which exhibit different properties. A dynamic family-of-questions analysis is developed to account for these phenomena. Briefly, a multiple- wh question generates a set of sub-questions, i.e., a family of questions, and then the set is transformed into a set of possible pair-list answers. Following Dynamic Plural Logic, the family of questions and possible pair-list answers encode different kinds of dependencies. Accessing the dependency encoded in a possible pair-list answer gives rise to question subordination, whereas accessing the dependency encoded in the family of questions gives rise to question telescoping.

Syntactic Nuclei in Dependency Parsing -- A Multilingual Exploration

Standard models for syntactic dependency parsing take words to be the elementary units that enter into dependency relations. In this paper, we investigate whether there are any benefits from enriching these models with the more abstract notion of nucleus proposed by Tesni\`{e}re. We do this by showing how the concept of nucleus can be defined in the framework of Universal Dependencies and how we can use composition functions to make a transition-based dependency parser aware of this concept. Experiments on 12 languages show that nucleus composition gives small but significant improvements in parsing accuracy. Further analysis reveals that the improvement mainly concerns a small number of dependency relations, including nominal modifiers, relations of coordination, main predicates, and direct objects.Comment: Accepted at EACL-202