On Sat, Jun 29, 2019 at 3:54 PM Xabush Semrie <[email protected]> wrote:
>
> why the heck would you need to "parse" atomese?
>
> What are you actually trying to do?
>
>
> I am converting it to JSON for graph visualization with Cytoscape.js for
> an annotation service. For example,
> (EvaluationLink
> (PredicateNode "expresses")
> (ListLink
> (GeneNode "MAP2K4")
> (MoleculeNode "Uniprot:Q5U0B8")))
>
> The above will be "parsed" into the following JSON
> {
> "data": {"source": "MAP2K4", "target": "Uniprot:Q5U0B8", "name":
> "expresses", "group": "edges"}
> }
>
>
Why not just dump directly from the atomspace?
> Especially since it already comes with a built-in parser?
>
>
> Maybe I am confusing something here, but I didn't know any parser existed
> for my use case.
>
? Of course there is. It's called "the atomspace".
--linas
>
>
> On Saturday, June 29, 2019 at 11:43:55 PM UTC+3, linas wrote:
>>
>> Dumb question: why the heck would you need to "parse" atomese? Especially
>> since it already comes with a built-in parser? What are you actually
>> trying to do? --linas
>>
>> On Sat, Jun 29, 2019 at 10:04 AM Xabush Semrie <[email protected]> wrote:
>>
>>> Hi,
>>>
>>> I have been working recently on LALR parser to parse atomese to
>>> JSON(code can be found here
>>> <https://github.com/Habush/annotation-scheme/blob/de66cd29c375321e5c7a14741a91c40ac40fb0b9/helpers/atomese-parser.scm#L98>).
>>> I initially used the same LALR parser generator used by GHOST found in
>>> *(system
>>> base lalr)* module with a similar lexer generator (in my case I
>>> precompiled the regex patterns for performance gain). However, I was
>>> getting very bad performance and it took way too long to parse moderately
>>> sized atomese files. It didn't help that the module didn't provided its own
>>> lexer generator and in the case of the GHOST code, the regex patterns were
>>> not precompiled which would further degrade the performance. As a result, I
>>> started looking at alternatives and found the nyacc project.
>>>
>>> After rewriting the code using nyacc, I found that the nyacc parser
>>> generator on average is 5-6X faster than the previous parser generator
>>> (which used by GHOST) for the same file. In addition to the performance
>>> improvement, it removes the need to provide a manually written lexer
>>> generator, has support for mid-rule context actions for complicated
>>> production rules, has a better debugging and "logging" capabilities and
>>> (although minor) doesn't require to list all the terminal symbols. Also the
>>> project is also being actively developed.
>>>
>>> Hence, I deduced the GHOST parser could also benefit the same
>>> performance improvements and thought sharing this here. I am happy to work
>>> on porting the LALR parser from the current one to nyacc if this gets
>>> traction.
>>>
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>>
>>
>> --
>> cassette tapes - analog TV - film cameras - you
>>
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