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Wrap everything in lime:Lexicon with some DublinCore terms #16

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@kernc kernc commented Dec 11, 2020

I'd expect some basic original dictionary metadata to persist the transformation.

I absolutely have no idea what I'm doing, and this is my first XSLT ever, so please kindly advise.

<xsl:apply-templates select="descendant::tei:title[text()]"/>
<xsl:apply-templates select="descendant::tei:author[text()]"/>
<xsl:apply-templates select="descendant::tei:date[text() | @when]"/>
<xsl:apply-templates select="descendant::tei:publisher[text()]"/>
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@kernc kernc Dec 11, 2020

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Templates for these have already been defined below, above the new licence template.

@kernc kernc mentioned this pull request Dec 11, 2020
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jmccrae commented Dec 11, 2020

Seems good from an OntoLex perspective. If @laurentromary is happy with this, we can merge.

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No problem apart the comments I made. Who is @kernc, BTW?

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kernc commented Dec 11, 2020

Just a passer by making sure language technologies are up to speed. 😝

From Lemon-Lime perspective, the Lexicon seems to be missing a further language:

<owl:Restriction>
    <owl:onProperty rdf:resource="http://www.w3.org/ns/lemon/lime#language"/>
    <owl:cardinality rdf:datatype="http://www.w3.org/2001/XMLSchema#nonNegativeInteger">1</owl:cardinality>
</owl:Restriction>

But unsure how to construct it, I just left it out. 😅

Updated the changed tests.

@kernc kernc marked this pull request as draft December 13, 2020 04:53
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kernc commented Dec 17, 2020

The prior version had issues. 😅 The DC terms transformation has now been amended to take into account only nodes in TEI/teiHeader/fileDesc, and to use only matching nodes' arbitrarily-nested normalized text content.

Priorly, I rebuilt the tests with a simple call to g.serialize(...) in test.convert_tei_to_ontolex().
They've now been went over and updated to produce a smaller, friendlier diff.

There are additional Lexicon properties I'd like to extract, namely dc:description, dc:subject, lime:language, but I'm not sure where in the TEI document to canonically find them. Welcome your thoughts.

@kernc kernc marked this pull request as ready for review December 17, 2020 09:07
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3 participants