nlp

Three-line (though non-standard) interlinear glossing

Still thinking about interlinear glossing for my language learning project. The leizig.js library is great but my use case isn’t really what the author had in mind. I really just need to display a unit consisting of the word as it appears in the text, the lemma for that word form, and (possibly) the part of speech. For academic linguistics purposes, what I have in mind is completely non-standard. The other issue with leizig.

Splitting text into sentences: Russian edition

Splitting text into sentences is one of those tasks that looks simple but on closer inspection is more difficult than you think. A common approach is to use regular expressions to divide up the text on punction marks. But without adding layers of complexity, that method fails on some sentences. This is a method using spaCy.

Stripping Russian syllabic stress marks in Python

I have written previously about stripping syllabic stress marks from Russian text using a Perl-based regex tool. But I needed a means of doing in solely in Python, so this just extends that idea. #!/usr/bin/env python3 def strip_stress_marks(text: str) -> str: b = text.encode('utf-8') # correct error where latin accented ó is used b = b.replace(b'\xc3\xb3', b'\xd0\xbe') # correct error where latin accented á is used b = b.replace(b'\xc3\xa1', b'\xd0\xb0') # correct error where latin accented é is used b = b.

Removing stress marks from Russian text

Previously, I wrote about adding syllabic stress marks to Russian text. Here’s a method for doing the opposite - that is, removing such marks (ударение) from Russian text. Although there may well be a more sophisticated approach, regex is well-suited to this task. The problem is that def string_replace(dict,text): sorted_dict = {k: dict[k] for k in sorted(dict)} for n in sorted_dict.keys(): text = text.replace(n,dict[n]) return text dict = { "а́" : "а", "е́" : "е", "о́" : "о", "у́" : "у", "я́" : "я", "ю́" : "ю", "ы́" : "ы", "и́" : "и", "ё́" : "ё", "А́" : "А", "Е́" : "Е", "О́" : "О", "У́" : "У", "Я́" : "Я", "Ю́" : "Ю", "Ы́" : "Ы", "И́" : "И", "Э́" : "Э", "э́" : "э" } print(string_replace(dict, "Существи́тельные в шве́дском обычно де́лятся на пять склоне́ний.