Shyam Upadhyay
- Publications
- Influence
Despite interest in using cross-lingual knowledge to learn word embeddings for various tasks, a systematic comparison of the possible approaches is lacking in the literature. We perform an extensive… Continue Reading
We present a reading comprehension challenge in which questions can only be answered by taking into account information from multiple sentences. We solicit and verify questions and answers for this… Continue Reading
Automatically solving algebra word problems has raised considerable interest recently. Existing state-of-the-art approaches mainly rely on learning from human annotated equations. In this paper, we… Continue Reading
Identifying mathematical relations expressed in text is essential to understanding a broad range of natural language text from election reports, to financial news, to sport commentaries to… Continue Reading
Cross-lingual Entity Linking (XEL) aims to ground entity mentions written in any language to an English Knowledge Base (KB), such as Wikipedia. XEL for most languages is challenging, owing to limited… Continue Reading
In this paper, we describe the University of Illinois (UI CCG) submission to the 2013 TAC KBP Event Argument Extraction (EAE), English Entity Discovery and Linking (EDL), and Slot Filler Validation… Continue Reading
Dataless text classification [Chang et al., 2008] is a classification paradigm which maps documents into a given label space without requiring any annotated training data. This paper explores a… Continue Reading
Cross-lingual Hypernymy Detection involves determining if a word in one language ("fruit") is a hypernym of a word in another language ("pomme" i.e. apple in French). The ability to detect hypernymy… Continue Reading
IEEE International Conference on Acoustics…
Spoken language understanding (SLU) is a component of goal-oriented dialogue systems that aims to interpret user's natural language queries in system's semantic representation format. While current… Continue Reading
Implementing a Natural Language Processing (NLP) system requires considerable engineering effort: creating data-structures to represent language constructs; reading corpora annotations into these… Continue Reading