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Found 19 papers, 2 papers with code
A Reference Dependency Bank for Analyzing Complex Predicates
When dealing with languages of South Asia from an NLP perspective, a problem that repeatedly crops up is the treatment of complex predicates.
lingvis.io - A Linguistic Visual Analytics Framework
We present a modular framework for the rapid-prototyping of linguistic, web-based, visual analytics applications.
Visualizing Linguistic Change as Dimension Interactions
This paper presents a significant extension of HistoBankVis, a multilayer visualization system which allows a fast and interactive exploration of complex linguistic data.
ParHistVis: Visualization of Parallel Multilingual Historical Data
The study of language change through parallel corpora can be advantageous for the analysis of complex interactions between time, text domain and language.
Using Meta-Morph Rules to develop Morphological Analysers: A case study concerning Tamil
This paper describes a new and larger coverage Finite-State Morphological Analyser (FSM) and Generator for the Dravidian language Tamil.
Dependency Parsing for Urdu: Resources, Conversions and Learning
This paper adds to the available resources for the under-resourced language Urdu by converting different types of existing treebanks for Urdu into a common format that is based on Universal Dependencies.
Representation Problems in Linguistic Annotations: Ambiguity, Variation, Uncertainty, Error and Bias
The development of linguistic corpora is fraught with various problems of annotation and representation.
Is that really a question? Going beyond factoid questions in NLP
Research in NLP has mainly focused on factoid questions, with the goal of finding quick and reliable ways of matching a query to an answer.
Automatized Detection and Annotation for Calls to Action in Latin-American Social Media Postings
While previous research has primarily looked at how calls-to-action (CTAs) were used in Twitter messages from non-profit organizations and protest mobilization, we are interested in identifying the linguistic cues used in CTAs found on Facebook and Twitter for an automatic identification of CTAs.
