We study the event detection problem using convolutional neural networks (CNNs) that overcome the two fundamental limitations of the traditional feature-based approaches to this t...
Spoken dialogue systems (SDS) typically require a predefined semantic ontology to train a spoken language understanding (SLU) module. In addition to the annotation cost, a key ch...
Yun-Nung Chen, William Yang Wang, Anatole Gershman...
In this paper, we present our Crossword Puzzle Resolution System (SACRY), which exploits syntactic structures for clue reranking and answer extraction. SACRY uses a database (DB) ...
We exploit the visual properties of concepts for lexical entailment detection by examining a concept’s generality. We introduce three unsupervised methods for determining a conc...
Douwe Kiela, Laura Rimell, Ivan Vulic, Stephen Cla...
We present an extension to incremental shift-reduce parsing that handles discontinuous constituents, using a linear classifier and beam search. We achieve very high parsing speed...
Automatic timeline summarization (TLS) generates precise, dated overviews over (often prolonged) events, such as wars or economic crises. One subtask of TLS selects the most impor...
Computing pairwise word semantic similarity is widely used and serves as a building block in many tasks in NLP. In this paper, we explore the embedding of the shortest-path metric...
Labeled data is not readily available for many natural language domains, and it typically requires expensive human effort with considerable domain knowledge to produce a set of la...