I want to extract location related keywords from raw text in python. I have already tried spacy but the results were not good and I just got names of countries while I want fine-grained location mentions like streets or neighborhoods in a city. I also have tried stanford NER but the problem is it is too slow and I need to produce my results with a good speed. Is there any package or library for python which can solve my problem? Also if there is any other suggestions which are not for python I will be glad to hear them.
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$\begingroup$ Hello Farzin, It would be better if you could explain the problem at hand in an elaborate fashion. With the problem, you could also outline the results you have achieved with Spacy and stanford NER. This could help contributors answer your questions better. $\endgroup$– Nischal HpCommented Sep 8, 2019 at 22:10
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$\begingroup$ thank you @NischalHp for your help, I will edit my question $\endgroup$– FarzinCommented Sep 9, 2019 at 11:57
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$\begingroup$ Related 10814. $\endgroup$– EdmundCommented Sep 12, 2019 at 2:14
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I fiund these two tools which can find geographical terms in a text file. mordecai: Full text geoparsing as a Python library. Extract the place names from a piece of text, resolve them to the correct place, and return their coordinates and structured geographic information.
, and CLIFF-CLAVIN: CLIFF-CLAVIN parses news articles and pulls out people, organizations and places mentioned.