You say that named entity recognition is not generalised beyond Mail, but the support library is there for anyone to use. See for example https://developer.apple.com/documentation/foundation/nslinguistictagger/iden... <https://developer.apple.com/documentation/foundation/nslinguistictagger/iden...>
Yes true.
In Python, you can use NLTK to do roughly the same.
There's no real point in reimplementing this stuff in Pharo. Just set up a separate process, send text to it, and receive results back.
I agree, that is an excellent option. "NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources <http://nltk.org/nltk_data/> such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum <http://groups.google.com/group/nltk-users>." Thanks for pointing NLTK. Great tool for sure. I agree that there no point in reimplementing but in this case of NLP, this might worth it as I think we have already all good foundations (Basic string manipulation, PP, Zn, XML, etcâ¦). The hard stuff is probably the integration of 100 corpora and lexical ressources (http://www.nltk.org/nltk_data/)... The thing is I need a lighter version, based on my own (growing) corpora (my experience). So Hernan solution, PP, or straight string processing would do the job. But thanks, this is something I will explore too (especially the luges ressources). Cheers, Cédrick
On Thu, 7 Mar 2019 at 22:53, Cédrick Béler <cdrick65@gmail.com <mailto:cdrick65@gmail.com>> wrote: Hi all,
Iâve often got the need to analyse some random unstructured text to discover (structured) information (in email for instance), to extract : - emails - telephone numbers - addresses - events - person names (according to a list of known persons), - etcâ¦
Apple do it in email for instance (strangely, this is not generalized).
So my questions are : - do we have something equivalent in Smalltalk/Pharo ? (I didnât find) - if not, what strategy would you use ? => I do really stupid text analysis (substrings, finding @, â¦, parsing according to the text structure when there is⦠kind of Soup parsingâ¦) => I feel this is a job for PetitParser ? And would be a nice feet to the new GToolkit.
All ideas or suggestions are welcome ;-)
TIA,
Cédrick