We make the case for developing a web of concepts by starting with the current view of web
(comprised of hyperlinked pages, or documents, each seen as a bag of words), extracting …

Wikipedia is a valuable resource, useful as a lingustic corpus or a dataset for many kinds of
research. We built corpora from Wikipedia articles and talk pages in the I5 format, a TEI …

Coarse-grained semantic categories such as supersenses have proven useful for a range of
downstream tasks such as question answering or machine translation. To date, no effort has …

We discuss the problem of ranking very many entities of different types. In particular we deal
with a heterogeneous set of types, some being very generic and some very specific. We …

We study the problem of finding sentences that explain the relationship between a named
entity and an ad-hoc query, which we refer to as entity support sentences. This is an …

In this chapter we provide our personal vision of what could be the next generation of Web
search engines, outlining the main research challenges that derive from it. This vision is …

We study sequential prediction models in cases where only fragments of the sequences are
annotated with the ground-truth. The task does not match the standard semi-supervised …

The paper presents a multi-document summarization system which builds companyspecific
summaries from a collection of financial news such that the extracted sentences contain …

Entity Retrieval (ER)—in comparison to classical search—aims at finding individual entities
instead of relevant documents. Finding a list of entities requires therefore techniques …

Semantic search seems to be an elusive and fuzzy target to many researchers. One of the
reasons is that the task lies in between several areas of specialization. In this extended …