def main(args):
words = args.word or []
categories = list(args.category or ())
dependencies = list(args.dependency or ())
if args.case_insensitive:
words = list(map(str.lower, words))
for spec in read_specs(args, converters=FROM_FORMAT):
if args.dependency:
spec.passages = annotate_udpipe(spec.passages, spec.udpipe) if spec.udpipe else \
annotate_all(spec.passages, as_array=True, replace=not spec.udpipe, lang=spec.lang)
t = tqdm(spec.passages, unit=" passages", desc="Finding")
if words:
t.set_postfix(words=",".join(words))
if categories:
t.set_postfix(categories=",".join(categories))
if dependencies:
t.set_postfix(dependencies=",".join(dependencies))
found = 0
filename = os.path.join(
spec.out_dir, "_".join(words + categories + dependencies) + ".txt")
with open(filename, "w", encoding="utf-8") as f:
for passage in t:
for terminal in passage.layer(layer0.LAYER_ID).all:
parent = terminal.parents[0]
word = terminal.text
if args.case_insensitive:
word = word.lower()
if (not words or word in words) and (
not categories or parent.ftag in categories) and (
not dependencies or get_annotation(
terminal, spec.udpipe) in dependencies):
print(passage.ID, parent.fparent, file=f)
found += 1
t.set_postfix(found=found)
print("Wrote '%s'" % filename)
def main(args):
if not args.as_array and not args.as_extra:
args.as_extra = True
for spec in read_specs(args, converters=FROM_FORMAT_NO_PLACEHOLDERS):
kwargs = dict(as_array=args.as_array,
as_extra=args.as_extra,
verbose=args.verbose,
lang=spec.lang)
passages = spec.passages
if spec.conllu:
passages = copy_annotation(passages,
spec.conllu,
by_id=args.by_id,
**kwargs)
elif spec.udpipe:
passages = annotate_udpipe(passages, spec.udpipe, **kwargs)
elif spec.stanfordnlp:
passages = annotate_stanfordnlp(passages, spec.stanfordnlp,
**kwargs)
for passage in annotate_all(passages if args.verbose else tqdm(
passages, unit=" passages", desc="Annotating " + spec.out_dir),
replace=spec.conllu
or not (spec.udpipe or spec.stanfordnlp),
**kwargs):
if passage.extra.get("format") == "amr" and args.as_array:
from semstr.conversion.amr import AmrConverter
AmrConverter.introduce_placeholders(passage)
write_passage(passage,
outdir=spec.out_dir,
verbose=args.verbose,
binary=args.binary)
def main(args):
for spec in read_specs(args, converters=FROM_FORMAT):
spec.passages = annotate_udpipe(spec.passages, spec.udpipe) if spec.udpipe else \
annotate_all(spec.passages, as_array=True, replace=not spec.udpipe, lang=spec.lang)
filename = os.path.join(spec.out_dir, "find.db")
with sqlite3.connect(filename) as conn:
c = conn.cursor()
c.execute("DROP TABLE terminals")
c.execute(
"CREATE TABLE terminals (pid, tid, text, ftag, fparent, dep)")
c.execute("CREATE INDEX idx_terminals_pid ON terminals (pid)")
c.execute("CREATE INDEX idx_terminals_text ON terminals (text)")
c.execute("CREATE INDEX idx_terminals_ftag ON terminals (ftag)")
c.execute("CREATE INDEX idx_terminals_dep ON terminals (dep)")
for passage in tqdm(spec.passages,
unit=" passages",
desc="Creating " + filename):
rows = []
for terminal in passage.layer(layer0.LAYER_ID).all:
parent = terminal.parents[0]
rows.append(
(passage.ID, terminal.ID, terminal.text, parent.ftag,
str(parent.fparent),
get_annotation(terminal, spec.udpipe)))
c.executemany("INSERT INTO terminals VALUES (?,?,?,?,?,?)",
rows)
conn.commit()
def main(args):
for spec in read_specs(args, converters=FROM_FORMAT):
if spec.udpipe:
spec.passages = annotate_udpipe(spec.passages, spec.udpipe, as_array=args.as_array, verbose=args.verbose)
elif spec.conllu:
spec.passages = copy_annotation(spec.passages, spec.conllu, as_array=args.as_array, verbose=args.verbose)
for passage in annotate_all(spec.passages if args.verbose else
tqdm(spec.passages, unit=" passages", desc="Annotating " + spec.out_dir),
as_array=args.as_array, replace=not spec.udpipe, lang=spec.lang,
verbose=args.verbose):
write_passage(passage, outdir=spec.out_dir, verbose=args.verbose, binary=args.binary)
def annotate_stanfordnlp(passages, model_name, as_array=True, as_extra=True, verbose=False, lang=None):
def _parser(conllu, *args, **kwargs):
del args, kwargs
import stanfordnlp
text = "\n".join(" ".join(line.split()[1] if line.strip() else line
for line in lines if line and not line.startswith("#"))
for lines in conllu if lines)
nlp = stanfordnlp.Pipeline(lang=lang, tokenize_pretokenized=True)
return nlp(text).conll_file.conll_as_string().splitlines()
yield from annotate_udpipe(passages, model_name, as_array=as_array, as_extra=as_extra, verbose=verbose, lang=lang,
parser=_parser)