Hi,

I had this idea for some time now but never got to test/write it down.
DBpedia extracts detailed context information in Quads (where possible) on where each triple came from, including the line number in the wiki text.
Although each DBpedia extractor is independent, using this context there is a small window for combining output from different extractors, such as the infobox statements we extract from Wikipedia and the very recent citation extractors we announced [1]

I attach a very small sample from the article about Germany where I filter out the related triples and order them by the line number they were extracted from e.g.

dbr:Germany dbo:populationTotal "82175700"^^xsd:nonNegativeInteger  <http://en.wikipedia.org/wiki/Germany?oldid=736355524#absolute-line=66&template=Infobox_country&property=population_estimate&split=1&wikiTextSize=10&plainTextSize=10&valueSize=8> .
<https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/2016/08/PD16_295_12411pdf.pdf;jsessionid=996EC2DF0A8D510CF89FDCBC74DBAE9F.cae2?__blob=publicationFile> dbp:isCitedBy dbr:Germany <http://en.wikipedia.org/wiki/Germany?oldid=736355524#absolute-line=66> .

Looking at the wikipedia article we see:
|population_estimate = 82,175,700<ref>{{cite web|url=https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/2016/08/PD16_295_12411pdf.pdf;jsessionid=996EC2DF0A8D510CF89FDCBC74DBAE9F.cae2?__blob=publicationFile|title=Population at 82.2 million at the end of 2015 – population increase due to high immigration|date=26 August 2016|work=destatis.de}}</ref>

Could this approach be a good candidate reference suggestions in Wikidata? 
(This particular one is already a reference but the anthem and GDP in the attachment are not for example)

There are many things that can be done to improve the matching but before getting into details I would like to see if this idea is worth exploring more or not

Cheers,
Dimitris

[1] http://www.mail-archive.com/dbpedia-discussion%40lists.sourceforge.net/msg07739.html

--
Dimitris Kontokostas
Department of Computer Science, University of Leipzig & DBpedia Association
Research Group: AKSW/KILT http://aksw.org/Groups/KILT