Kingsley and Doug, (01)
The Quepy developers use the NLTK toolkit, which is an open-source
set of Python-based software for NLP processing. It's widely used
for teaching purposes. But it is not state of the art NLP software. (02)
KI
> it's only using DBpedia whereas if it used the LOD cloud cache
> there would be a much broader knowledgebase. (03)
Google answered every one of my five questions, but Quepy could
only answer one of them. I also tried Bing, which did just
as well as Google on all five. (04)
In fact, Bing got a better answer for the question "When did
the Revolutionary War end?" In addition to hits that were similar
to Google's, Bing gave the following answer above the list of hits: (05)
Bing
> The American Revolutionary War began on Wednesday, April 19, 1775
> and ended on Wednesday, September 3, 1783. (06)
DF
> I asked for the President of the UK, and since the SPARQL query
> was for a leader, not a president, the answers returned were
> David Cameron and Queen Elizabeth II. (07)
I typed "Who is the president of the UK?" to Google and Bing.
Both of them found the following plus some other relevant hits: (08)
Bing and Google
> Who is the president of the United Kingdom - The Q&A wiki
> wiki.answers.com › … › United Kingdom › UK Politics
>
> The United Kingdom is a parliamentary constitutional monarchy
> and has no president. HM Queen Elizabeth II is Head of State.
> The Right Honourable David Cameron MP is ... (09)
Of course, Google and Microsoft (Bing) are multi-billion dollar
corporations with huge R & D budgets. Quepy is OK for homework
exercises in a course on NLP. (010)
DF
> It seems to generate SPARQL without using any ontology. (011)
I read some of the Quepy documentation, which indicates that
they do recognize "classes" and "subclasses". But Google,
Bing, and many other commercial companies have much richer
resources. (012)
KI
> To conclude, the key point I sought to make via this post is that
> natural language based SPARQL generation is an emerging frontier. (013)
I doubt that. Neither Google nor Bing use RDF, SPARQL, or OWL.
Instead, they do pattern matching directly to the raw, unannotated
natural language texts. (014)
I'll admit that there is a large and growing corpus of tagged
documents, for which RDF processing can be useful. But the raw NL
documents are growing at a much faster rate than the tagging. (015)
KI
> that never happened on the SQL front, in any kind of webby way, of
> course, I would happily look at a live Web accessible SQL based system
> to see if it can match the most basic SPARQL functionality demonstrated
> by Quepy fronting SPARQL (016)
SQL has a superset of the expressive power of RDF. People had developed
very sophisticated NLP query systems for DB queries 30 years ago. For
examples, see http://www.jfsowa.com/pubs/futures.pdf . Most of those
systems never became profitable or they remained niche products. (017)
But some of them have been connected to speech systems for those
annoying automated telephone systems. Replacing SQL with SPARQL
will do nothing to make them less annoying. (018)
As for webifying a version of SQL, that would be fairly easy to do.
In Fact, Tim B-L included SQL as one of the languages that had to be
supported. (See his DAML proposal of 2000.) Oracle and IBM do that
with their products. But the clueless academics who jumped on the
DAML bandwagon refused to support SQL. (019)
John (020)
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