At present, adapting an Information Extraction system to new topics is
an expensive and slow process, requiring some knowledge engineering
for each new topic. We propose a new paradigm of Information
Extraction which operates 'on demand' in response to a user's
query. On-demand Information Extraction (ODIE) aims to completely
eliminate the customization effort. Given a user's query, the
system will automatically create patterns to extract salient relations
in the text of the topic, and build tables from the extracted
information using paraphrase discovery technology. It relies on recent
advances in pattern discovery, paraphrase discovery, and extended
named entity tagging.  I will show you a demo system, which produce a
table in less than a minute for any give queries.
<p>

S.Sekine "On-Demand Information Extraction" (COLING-ACL 07)
<a href="http://nlp.cs.nyu.edu/sekine/papers/coling06.pdf">
http://nlp.cs.nyu.edu/sekine/papers/coling06.pdf</a>
<p>

I will also give a brief talk about Ngram Search Engine and the Web
People Search (WePS). Ngram search engine is a tool to search ngrams
which match user's ngram query which can include arbitrary wildcards
in a tenth of a second. It is a useful tool for semantic knowledge
discovery.  WePS is a task to disambiguate search results of people
name. At the first evaluation at SemEval-2007, 16 groups have
participated. We are preparing the second evaluation which includes
people's attribution extraction task.