We introduce C-PHRASE, a distributional semantic model that learns word representations by optimizing context prediction for phrases at all levels in a syntactic tree, from single words to full sentences. C-PHRASE outperforms the state-of-theart C-BOW model on a variety of lexical tasks. Moreover, since C-PHRASE word vectors are induced through a compositional learning objective (modeling the c...

This paper argues that wh-in situ is interpreted in its original position. Focusing on the ambiguity of how many sentences, it shows that the semantic behavior of wh in-situ can be explained without postulating LF (phrasal) movement. It is then pointed out that the fact that wh-phrases in situ lack anti-reconstruction effects follows directly from this non movement approach. The paper also show...

Prominent neurobiological models of language follow the widely accepted assumption that language comprehension requires two principal mechanisms: a lexicon storing the sound-to-meaning mapping of words, primarily involving bilateral temporal regions, and a combinatorial processor for syntactically structured items, such as phrases and sentences, localized in a left-lateralized network linking l...

The present paper describes a methodology for automatic text summarisation of Greek texts which combines terminology extraction and sentence spotting. Since generating abstracts has proven a hard NLP task of questionable effectiveness, the paper focuses on the production of a special kind of abstracts, called extracts: sets of sentences taken from the original text. These sentences are selected...

In this paper, we propose a novel strategy which is designed to enhance the accuracy of the parser by simplifying complex sentences before parsing. This approach involves the separate parsing of the constituent sub-sentences within a complex sentence. To achieve that, the divide-and-conquer strategy first disam-biguates the roles of the link words in the sentence and segments the sentence based...

Novice users engaged in task-oriented dialogues with an adviser to learn how to use an unfamiliar statistical package. The users', task was analyzed and a task structure was derived. The task structure was used to segment the dialogue into subdialogues associated with the subtasks of the overall task. The representation of the dialogue structure into a hierarchy of subdialogues, partly correspo...

Question Generation (QG) and Question Answering (QA) are some of the many challenges for natural language understanding and interfaces. As humans need to ask good questions, the potential benefits from automated QG systems may assist them in meeting useful inquiry needs. In this paper, we consider an automatic Sentence-to-Question generation task, where given a sentence, the Question Generation...

Sentence compression is a task of creating a short grammatical sentence by removing extraneous words or phrases from an original sentence while preserving its meaning. Existing methods learn statistics on trimming context-free grammar (CFG) rules. However, these methods sometimes eliminate the original meaning by incorrectly removing important parts of sentences, because trimming probabilities ...

Online blog data provide numerous benefits over clinical and laboratory studies, including increased sample size and more genuine responses. By investigating the number of feeling words that a blogger uses in a blog sentence, we can characterize the degree to which individuals elaborate on their emotional experiences. In this study, data were obtained from the website, wefeelfine.org, which col...