Review Comment:
I had difficulties in reading the paper, but I think I got the main ideas. Unfortunately the web pages http://lego-wordlists.googlecode.com/files/LegoUnified.rdf and http://code.google.com/p/lego-wordlists/downloads/, mentioned in the submission are not reachable.
If I understand well the direction: I have a meta conceptlist that establishes similarities between concepts used in distinct word lists which are pointing to concepts, and so help in establishing cross-lingual links between those word lists.
Here a first point: the authors compare their approach with DBpedia, but I think that a comparison with various WordNet families (also available in RDF and published in the LOD) is more appropriate.
A main question is then how and why the LEGO Concepticon differs from SUMO/WordNet like organisation of lexical resources.
Another topic: I am not sure if the keys used in Wordlists are necessarily meanings and the values only wordforms, but what intended is, is clear: how does one express the English word "man" in French: "homme".
If we want to keep the vocabulary used in the submission: if we reverse the relation, going from French to English, do we map from a word form to a concept? Or do we need another (French) conceptualization so that the French concept "Homme" is linked to both "man" and "human being" ?
In any case I do not think that when wordlists are created, those aspects are considered by the creators. Looks more like easy to handle very basic specific translation helps for readers of a text.
Not sure if the presence or not of grammatical information is important in the distinction between wordlist and dictionary entries. But the fact that "chien" is associated to the concept "DOG" is a semantic information I guess, although this is denied by the authors.
"As will be seen, our linked data representation of wordlists deviates from the traditional model in not directly containing concept labels but, rather, references to concepts described via labels in an external concepticon." Is this not the way RDF encoded taxonomies / ontologies are working? Why introduce here the "concepticon" topic? One can take any wordlist and link its elements to concepts in an existing or to be created taxonomy/ontology. Or not?
"The structure of the concepticon is schematized in
Figure 2. The concepticon is a container (associated
with metadata not depicted in the figure), which consists
of unified concepts which are themselves containers
for concepts from the concepticons". Hard to understand. Looks circular!
"As can be seen, the information encoded in these
wordlists is quite sparse~for instance, it only includes
concept identifiers, not concept labels. Therefore, in
order to reconstruct the information associated with
traditional wordlists (as in (1)), the unified concepticon
must be merged with the wordlist." Why were the concept labels lost. I do not understand.... Why not include them from the very beginning? And what are concept labels in fact.....?
So again: Not clear how the LEGO fulfil other goals as the Universal Word Net effort.
No idea on how concepts are encoded.
Can LEGO not be entirely expressed in SKOS-XL?
The work here seems to be very idio-syncratic.
Also no indications of level of automation, number of items/lexical entries etc. (but I could not reach the quoted web pages)
Most of the negative comments are due to the fact that I was looking to a contribution to the Multilingual Linked Open Data, and the submission doesn't seem to offer a concrete contribution or a relevant data set by now. My comments are not about the intrinsic value of the word described.
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