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commented and refactored read_wiktionary.py

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aarneranta
2023-09-15 14:48:23 +02:00
parent edecc3fe57
commit 73f0b8ef00
2 changed files with 133 additions and 86 deletions
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203
src/arabic/wiktionary/read_wiktionary.py
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@@ -31,7 +31,7 @@ create GF files:
automatic evaluation:
$ gf -make MorphoDictAra.gf
$ python3 read_wiktionary.py gf-map >function_sources_arabic.jsonl
$ python3 read_wiktionary.py gf-map >source_of_MorphoDictAra.jsonl
$ python3 read_wiktionary.py eval
TODO:
@@ -42,8 +42,6 @@ TODO:
"""
MODE = ''
if __name__ == '__main__':
@@ -53,8 +51,9 @@ if __name__ == '__main__':
MODE = sys.argv[1] #
# step 1: extract data from this file using the raw option
# step 1: extract Arabic data from this file using the raw option
WIKTIONARY_DUMP = 'raw-wiktextract-data.json.gz'
EXTRACTED_LANGUAGE = 'Arabic'
# the following file is generated.
# in the sequel, use this file with gf-abs or gf-cnc option
@@ -62,24 +61,18 @@ FILTERED_WIKT = 'wikt_arabic.jsonl'
# map each successfully extracted GF function to its source record in Wiktionary
# created with option gf-map
FUNCTION_SOURCE_MAP = 'function_sources_arabic.jsonl'
FUNCTION_SOURCE_MAP = 'source_of_MorphoDictAra.jsonl'
# created with $ gf -make MorphoDictAra.gf
PGF_FILE = 'MorphoDictAraAbs.pgf'
# module to linearize with
CONCRETE_MODULE = 'MorphoDictAra'
def read_function_source_map():
with open(FUNCTION_SOURCE_MAP) as file:
sourcemap = {}
for line in file:
try:
obj = json.loads(line)
sourcemap[obj['fun']] = obj['source']
except:
continue
return sourcemap
# read a gzipped jsonl file (one object per line),
# showing lines where one of a list of languages is present
# This can be sampled to one of 100k lines by default, 1 for total recall.
def get_gzip_json(file, sample=100000, langs=[]):
with gzip.open(file) as decompressed:
n = 0
@@ -91,10 +84,13 @@ def get_gzip_json(file, sample=100000, langs=[]):
print(line.decode("utf-8"))
# print(n)
if MODE == 'raw':
get_gzip_json(WIKTIONARY_DUMP, 1, ['Arabic'])
# to perform the first step of data extraction, pipe this into a file:
# python3 read_wiktionary.py raw >wikt_arabic.jsonl
if MODE == 'raw':
get_gzip_json(WIKTIONARY_DUMP, 1, [EXTRACTED_LANGUAGE])
exit()
# https://en.wikipedia.org/wiki/Buckwalter_transliteration
buckwalter_dict = {
@@ -177,19 +173,22 @@ def reorder_shadda(s):
return from_buckwalter(to_buckwalter(s).replace('a~', '~a').replace('u~', '~u').replace('i~', '~i'))
# quote forms but not parameters
# quote word forms but not parameters
def quote_if(s, cond=is_arabic, change=reorder_shadda):
if cond(s):
return '"' + change(s) + '"'
else:
return s
# generate word_d_C functions starting with d=0, but show d only when >= 1
def gf_fun(s, pos, disamb=0):
discrim = '_' + str(disamb) if disamb else ''
return ''.join(["'", s, discrim, "_", pos, "'"])
rgl_features = {
# mapping from GF to Wikt features
arabic_rgl_features = {
# V
'VPerf': 'perfective',
'Act': 'active',
@@ -225,61 +224,21 @@ rgl_features = {
}
# obsolote:
# format of GF table: MorphoDictAra: s (VPerf Act (Per3 Masc Sg)) : أَجْرََ
# coming from 'l -treebank -table'
# now used:
# {'s (AComp Def Bare)': 'الأَيَُونَانِ'}
# coming from tabularLinearize
def compare_tables(gf, wikt, fun):
report = {}
for pair in gf.items():
gf_form = pair[1]
gf_tags = tuple(word for word in
pair[0].replace('(', ' ').replace(')', ' ').split()
if word in rgl_features)
if not gf_tags:
continue
wikt_tags = {rgl_features[tag] for tag in gf_tags}
wikt_form = None
wikt_descr = None
for form, descr in wikt:
if all([tag in descr for tag in wikt_tags]):
wikt_form = reorder_shadda(form)
wikt_descr = descr
break
report[gf_tags] = {
'gf_form': gf_form,
'wikt_form': wikt_form,
'gf_form_rom': to_buckwalter(gf_form) if gf_form else None,
'wikt_form_rom': to_buckwalter(wikt_form) if wikt_form else None,
'wikt_descr': wikt_descr
}
if wikt_form:
report[gf_tags]['voc_match'] = int(normal(gf_form) == normal(wikt_form))
report[gf_tags]['unvoc_match'] = int(normal(unvocalize(gf_form)) == normal(unvocalize(wikt_form)))
ritems = tuple(report.items()) # need an unmutable structure, because otherwise ints are added to items
report['fun'] = fun
report['total_found'] = len([f for f, v in ritems if v['wikt_form'] is not None ])
report['total_voc'] = sum([v.get('voc_match', 0) for f, v in ritems])
report['total_unvoc'] = sum([v.get('unvoc_match', 0) for f, v in ritems])
return report
def wikt_forms_for_pos(obj):
# the inflection forms in a wiktionary entry
def wikt_forms_from_obj(obj):
return {
form['form']:
form.get('tags', []) for
form in obj.get('forms', []) if
'romanization' not in form.get('tags', []) and
is_arabic(form['form'])
}.items()
}
# selection of forms for a given POS from Wikt: noun, adj, or verb
# return a linearization function
def forms_for_pos(obj):
forms = wikt_forms_for_pos(obj)
forms = wikt_forms_from_obj(obj).items()
if obj['pos'] == 'noun':
lemma = [form[:-1] for form, descr in forms
if all([w in descr for w in ['construct', 'nominative', 'singular']])][:1]
@@ -345,46 +304,60 @@ def forms_for_pos(obj):
if obj['root'] and obj['root'][0].strip():
gf_entry['args']['root'] = obj['root']
args = [r + ' = ' + quote_if(x[0]) for r, x in gf_entry['args'].items() if x]
gf_entry['lin'] = 'wmk' + gf_entry['cat'] + ' {' + ' ; '.join(args) + '}'
gf_entry['lin'] = 'wmk' + gf_entry['cat'] + ' {' + ' ; '.join(sorted(args)) + '}'
return gf_entry
# "root": ["ش ر ح (š-r-ḥ)"]
def find_root(s):
return ''.join([c for c in s if is_arabic(c)])
# GF code generation
# start with the header of the desired GF module
if MODE == 'gf-abs':
print('abstract MorphoDictAraAbs = Cat ** {')
if MODE == 'gf-cnc':
print('concrete MorphoDictAra of MorphoDictAraAbs = CatAra ** open ParadigmsAra in {')
# go through the Arabic Wiktionary entries
# generate functions with unique names
if MODE.startswith('gf') or MODE=='json':
with open(FILTERED_WIKT) as file:
seen_gf_funs = {}
seen_gf_funs = {} # to disambiguate names if needed
number = 1
for line in file:
try:
obj = json.loads(line)
except:
continue
number += 1
number += 1 # if you find the same word_C again, mark it word_1_C
# the root (three radicals) is found in this place if at all
root = [find_root(t['expansion']) for
t in obj.get('etymology_templates', []) if
t.get('name', None) =='ar-root'][:1]
obj['root'] = root
# only take entries that are marked as lemmas
if 'Arabic lemmas' in obj.get('categories', []):
entry = {
'pos': obj['pos'],
'forms': forms_for_pos(obj),
'all_forms': wikt_forms_from_obj(obj),
'senses': [sense['glosses'] for sense in obj.get('senses', [])
if 'glosses' in sense]
}
# entry['n_forms'] = len(entry['forms'])
# print(entry['pos'], entry['n_forms'])
# if you only want to see the Wikt information used GF generation
if MODE == 'json':
print(json.dumps(entry, ensure_ascii=False))
# if you want to proceed to GF generation
if MODE.startswith('gf'):
lemma = entry['forms'].get('lemma', None)
@@ -394,22 +367,73 @@ if MODE.startswith('gf') or MODE=='json':
discrim = seen_gf_funs.get((lemma, cat), 0)
fun = gf_fun(lemma, cat, discrim)
# abstract syntax, save in MorphoDictAraAbs.gf
if MODE == 'gf-abs':
print('fun', fun, ':', cat, ';', '--', number, entry['senses'])
if MODE == 'gf-cnc':
# concrete syntax, save in MorphoDictAra.gf
elif MODE == 'gf-cnc':
print('lin', fun, '=', lin, ';')
if MODE == 'gf-map':
mapitem = {'fun': fun, 'source': obj}
# function-source map, save in source_of_MorphoDictAra.jsonl
elif MODE == 'gf-map':
mapitem = {'fun': fun, 'source': wikt_forms_from_obj(obj)}
print(json.dumps(mapitem, ensure_ascii=False))
seen_gf_funs[(lemma, cat)] = discrim + 1
seen_gf_funs[(lemma, cat)] = discrim + 1 # next word_d_C will get a new number
# to do: rename duplicate function names: of 13762 names, 12946 are unique
if MODE.startswith('gf'):
# terminate the GF file with a closing brace
if MODE in ['gf-abs', 'gf-cnc']:
print('}')
# evaluation:
# linearize all words to tables
# compare them to the forms found in Wiktionary
# report on matches
# format of GF table:
# {'s (AComp Def Bare)': 'الأَيَُونَانِ'}
# coming from pgf tabularLinearize
def compare_tables(gf, wikt, fun, show_buckwalter=True):
report = {}
for pair in gf.items():
gf_form = pair[1]
gf_params = pair[0]
gf_tags = tuple(word for word in
pair[0].replace('(', ' ').replace(')', ' ').split()
if word in arabic_rgl_features)
if not gf_tags:
continue # if gf_tags match no Wikt tags, do not include this form
wikt_tags = {arabic_rgl_features[tag] for tag in gf_tags}
wikt_form = None
wikt_descr = None
for form, descr in wikt:
if all([tag in descr for tag in wikt_tags]):
wikt_form = reorder_shadda(form)
wikt_descr = descr
break
report[gf_tags] = { # flat param description with only Wikt-relevant tags
'gf_params': gf_params, # full param description
'gf_form': gf_form,
'wikt_form': wikt_form,
'wikt_descr': wikt_descr
}
if show_buckwalter:
report[gf_tags]['gf_form_rom'] = to_buckwalter(gf_form) if gf_form else None,
report[gf_tags]['wikt_form_rom'] = to_buckwalter(wikt_form) if wikt_form else None,
if wikt_form:
report[gf_tags]['voc_match'] = int(normal(gf_form) == normal(wikt_form))
report[gf_tags]['unvoc_match'] = int(normal(unvocalize(gf_form)) == normal(unvocalize(wikt_form)))
ritems = tuple(report.items()) # need an unmutable structure, because otherwise ints are added to items
report['fun'] = fun
report['total_found'] = len([f for f, v in ritems if v['wikt_form'] is not None ])
report['total_voc'] = sum([v.get('voc_match', 0) for f, v in ritems])
report['total_unvoc'] = sum([v.get('unvoc_match', 0) for f, v in ritems])
return report
def eval_all(gr, funmap, concrete=CONCRETE_MODULE):
lang = gr.languages[CONCRETE_MODULE]
funs = gr.functions
@@ -419,13 +443,14 @@ def eval_all(gr, funmap, concrete=CONCRETE_MODULE):
if funn not in funmap:
print(funn, 'not found')
continue
wikt = wikt_forms_for_pos(funmap[funn])
wikt = funmap[funn].items()
gf = lang.tabularLinearize(pgf.Expr(fun, []))
report = compare_tables(gf, wikt, fun)
reports.append(report)
return reports
# in the summary report: print the first error if anything gets wrong
def first_error(report):
for f, v in report.items():
if 'voc_match' in v:
@@ -433,6 +458,20 @@ def first_error(report):
return f, v
# having stored the Wiktionary object for each GF function
# read it back from a file
def read_function_source_map():
with open(FUNCTION_SOURCE_MAP) as file:
sourcemap = {}
for line in file:
try:
obj = json.loads(line)
sourcemap[obj['fun']] = obj['source']
except:
continue
return sourcemap
if MODE.startswith('eval'):
gr = pgf.readPGF(PGF_FILE)
print('using', PGF_FILE)
@@ -443,6 +482,10 @@ if MODE.startswith('eval'):
if MODE == 'eval-verbose':
for line in report.items():
print(line)
if MODE == 'eval-tables':
for gftags, value in report.items():
if v := value['wikt_form']:
print(' ', value['gf_params'][2:], '=>', '"' + v + '" ;')
else:
if report['total_found'] == 0:
verdict = 'NOT_FOUND'

6
src/arabic/wiktionary/to_wordnet.py
View File

@@ -4,7 +4,11 @@ import json
# to run: python3 to_wordnet.py >arabic-wn-morpho.jsonl
# the following are assumed
# from https://www.grammaticalframework.org/~krasimir/arabic.tsv.gz
WN_TSV = 'arabic.tsv'
# built as explained in ./read_wiktionary.py
MORPHO_GF = 'MorphoDictAraAbs.gf'
def is_arabic(s):
@@ -36,7 +40,7 @@ with open(WN_TSV) as wnfile:
## wnreader = csv.reader(wnfile, delimiter='\t')
for row in wnfile:
## word = row[-1].strip() # does not show tha arabic, but the second-last word
word = get_arabic(row)
word = unvocalize(get_arabic(row))
wnfun = row.split()[0]
cat = [c for c in wnfun if c.isalpha()][-1] # the last letter; the dict only contains N, A, V
funs = funmap.get((word, cat), [])