11 citations · 12 across the 4 of their papers we have counts for
6 papers · 1 filter
Aspectuality Across Genre: A Distributional Semantics Approach
Thomas Kober, Malihe Alikhani, Matthew Stone +1
The interpretation of the lexical aspect of verbs in English plays a crucial role for recognizing textual entailment and learning discourse-level inferences. We show that two eleme…
STAR: A Schema-Guided Dialog Dataset for Transfer Learning
Johannes E. M. Mosig, Shikib Mehri, Thomas Kober
We present STAR, a schema-guided task-oriented dialog dataset consisting of 127,833 utterances and knowledge base queries across 5,820 task-oriented dialogs in 13 domains that is e…
Going Beyond T-SNE: Exposing \texttt{whatlies} in Text Embeddings
Vincent D. Warmerdam, Thomas Kober, Rachael Tatman
We introduce whatlies, an open source toolkit for visually inspecting word and sentence embeddings. The project offers a unified and extensible API with current support for a range…
Data Augmentation for Hypernymy Detection
Thomas Kober, Julie Weeds, Lorenzo Bertolini +1
The automatic detection of hypernymy relationships represents a challenging problem in NLP. The successful application of state-of-the-art supervised approaches using distributed r…
Temporal and Aspectual Entailment
Thomas Kober, Sander Bijl de Vroe, Mark Steedman
Inferences regarding "Jane's arrival in London" from predications such as "Jane is going to London" or "Jane has gone to London" depend on tense and aspect of the predications. Ten…
One Representation per Word - Does it make Sense for Composition?
Thomas Kober, Julie Weeds, John Wilkie +2
In this paper, we investigate whether an a priori disambiguation of word senses is strictly necessary or whether the meaning of a word in context can be disambiguated through compo…