2 code implementations • 11 Apr 2020 • Varada Kolhatkar, Nithum Thain, Jeffrey Sorensen, Lucas Dixon, Maite Taboada
The quality of the annotation scheme and the resulting dataset is evaluated using measurements of inter-annotator agreement, expert assessment of a sample, and by the constructiveness sub-characteristics, which we show provide a proxy for the general constructiveness concept.
no code implementations • CL 2018 • Varada Kolhatkar, Adam Roussel, Stefanie Dipper, Heike Zinsmeister
Most of the existing approaches to anaphora annotation and resolution focus on nominal-antecedent anaphora, classifying many of the cases where the antecedents are syntactically non-nominal as non-anaphoric.
no code implementations • WS 2018 • Massimo Poesio, Yulia Grishina, Varada Kolhatkar, Nafise Moosavi, Ina Roesiger, Adam Roussel, Fabian Simonjetz, Alex Uma, ra, Olga Uryupina, Juntao Yu, Heike Zinsmeister
The most distinctive feature of the corpus is the annotation of a wide range of anaphoric relations, including bridging references and discourse deixis in addition to identity (coreference).
no code implementations • WS 2017 • Varada Kolhatkar, Maite Taboada
We examine the extent to which we are able to automatically identify constructive online comments.
no code implementations • WS 2017 • Varada Kolhatkar, Maite Taboada
We discuss the characteristics of constructive news comments, and present methods to identify them.