62 citations · 94 across the 6 of their papers we have counts for
6 papers
Parsing Universal Dependencies without training
Héctor Martínez Alonso, Željko Agić, Barbara Plank +1
We propose UDP, the first training-free parser for Universal Dependencies (UD). Our algorithm is based on PageRank and a small set of head attachment rules. It features two-step de…
When is multitask learning effective? Semantic sequence prediction under varying data conditions
Héctor Martínez Alonso, Barbara Plank
Multitask learning has been applied successfully to a range of tasks, mostly morphosyntactic. However, little is known on when MTL works and whether there are data characteristics…
When silver glitters more than gold: Bootstrapping an Italian part-of-speech tagger for Twitter
Barbara Plank, Malvina Nissim
We bootstrap a state-of-the-art part-of-speech tagger to tag Italian Twitter data, in the context of the Evalita 2016 PoSTWITA shared task. We show that training the tagger on nati…
Semantic Tagging with Deep Residual Networks
Johannes Bjerva, Barbara Plank, Johan Bos
We propose a novel semantic tagging task, sem-tagging, tailored for the purpose of multilingual semantic parsing, and present the first tagger using deep residual networks (ResNets…
Keystroke dynamics as signal for shallow syntactic parsing
Barbara Plank
Keystroke dynamics have been extensively used in psycholinguistic and writing research to gain insights into cognitive processing. But do keystroke logs contain actual signal that…
What to do about non-standard (or non-canonical) language in NLP
Barbara Plank
Real world data differs radically from the benchmark corpora we use in natural language processing (NLP). As soon as we apply our technologies to the real world, performance drops.…