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152 lines
5.7 KiB
152 lines
5.7 KiB
from corpusparser import Sentence
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from pathlib import Path
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import re
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from lxml import etree
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# Read input file(.xml, .json; kres or ssj500k).
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# Create an iterator that outputs resulting sentences (python dict format).
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class Parser():
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def __init__(self, corpus, infiles):
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if corpus == "kres":
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self.kres_folder = Path(infiles[0])
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self.kres_srl_folder = Path(infiles[1])
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elif corpus == "ssj":
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self.ssj_file = Path(infiles[0])
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else:
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raise ValueError("Argument corpus should be 'ssj' or 'kres'.")
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self.corpus = corpus
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self.W_TAGS = ['w']
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self.C_TAGS = ['c']
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self.S_TAGS = ['S', 'pc']
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def parse_jos_links(self, sent_el):
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if self.corpus == "kres":
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return self.parse_jos_links_kres(sent_el)
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else:
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return self.parse_jos_links_ssj(sent_el)
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def parse_ssj_target_arg(self, text):
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# from: 0, to: 6
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# <link ana="syn:modra" target="#ssj1.1.3 #ssj1.1.3.t6"/>
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# from: 6, to: 7
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# <link ana="syn:dol" target="#ssj1.1.3.t6 #ssj1.1.3.t7"/>
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lst = [x.split(".")[-1] for x in text.split(" ")]
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return [int(x[1:] if x[0] == "t" else 0) for x in lst]
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def parse_jos_links_kres(self, sent_el):
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lgrps = sent_el.findall(".//links")
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if len(lgrps) < 1:
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raise IOError("Can't find links.")
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res_links = []
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for link in lgrps[0]:
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res_links += [{
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"from": int(link.get("from").split(".")[-1]),
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"afun": link.get("afun"),
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"to": int(link.get("dep").split(".")[-1]),
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}]
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return res_links
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def parse_jos_links_ssj(self, sent_el):
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lgrps = sent_el.findall(".//linkGrp")
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if len(lgrps) < 1:
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# print(etree.tostring(sent_el))
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raise IOError("Can't find links.")
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res_links = []
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for link in lgrps[0]:
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print(link)
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tar = self.parse_ssj_target_arg(link.get("target"))
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res_links += [{
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"from": tar[0],
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"afun": link.get("ana").split(":")[1],
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"to": [1],
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}]
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return res_links
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def parse(self):
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if self.corpus == "kres":
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print("parse kres: TODO")
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else:
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self.parse_xml_file(self.ssj_file)
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def parse_xml_file(self, filepath):
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res_dict = {}
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with filepath.open("rb") as fp:
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# remove namespaces
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bstr = fp.read()
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utf8str = bstr.decode("utf-8")
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utf8str = re.sub('\\sxmlns="[^"]+"', '', utf8str, count=1)
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utf8str = re.sub(' xml:', ' ', utf8str)
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root = etree.XML(utf8str.encode("utf-8"))
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divs = [] # in ssj, there are divs, in Kres, there are separate files
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if self.corpus == "kres":
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divs = [root]
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else:
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divs = root.findall(".//div")
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# parse divs
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for div in divs:
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f_id = div.get("id")
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# parse paragraphs
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for p in div.findall(".//p"):
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p_id = p.get("id").split(".")[-1]
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# parse sentences
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for s in p.findall(".//s"):
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s_id = s.get("id").split(".")[-1]
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sentence_text = ""
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sentence_tokens = []
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# parse tokens
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for el in s.iter():
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if el.tag in self.W_TAGS:
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el_id = el.get("id").split(".")[-1]
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if el_id[0] == 't':
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el_id = el_id[1:] # ssj W_TAG ids start with t
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sentence_text += el.text
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sentence_tokens += [{
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"word": True,
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"tid": int(el_id),
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"text": el.text,
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"lemma": el.get("lemma"),
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"msd": (el.get("msd") if self.corpus == "kres"
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else el.get("ana").split(":")[-1]),
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}]
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elif el.tag in self.C_TAGS:
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# only Kres' C_TAGS have ids
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el_id = el.get("id") or "none"
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el_id = el_id.split(".")[-1]
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sentence_text += el.text
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sentence_tokens += [{
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"word": False,
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"tid": el_id,
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"text": el.text,
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}]
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elif el.tag in self.S_TAGS:
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# Kres' <S /> doesn't contain .text
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sentence_text += " "
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else:
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# pass links and linkGroups
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pass
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sentence_id = "{}.{}.{}".format(f_id, p_id, s_id)
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# make a generator instead of holding the whole corpus in memory
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if sentence_id in res_dict:
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raise KeyError("duplicated id: {}".format(sentence_id))
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res_dict[sentence_id] = {
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"sid": sentence_id,
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"text": sentence_text,
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"tokens": sentence_tokens,
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"jos_links": self.parse_jos_links(s)
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}
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print(res_dict[sentence_id])
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break
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return res_dict
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