# ******************************************************************************
# Copyright 2017-2018 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
import re
# This file contains adapted open sourced code, publicly available at:
# https://github.com/elikip/bist-parser/blob/master/bmstparser/src/utils.py
# Things that were changed from the original:
# 1) Added input validation
# 2) Updated function and object names to dyNet 2.0.2 and Python 3
# 3) Removed external embeddings option
# 4) Reformatted code and variable names to conform with PEP8
# 5) Added dict_to_obj()
# 6) Added option for train() to get ConllEntry input
# 7) Added legal header
NUMBER_REGEX = re.compile("[0-9]+|[0-9]+\\.[0-9]+|[0-9]+[0-9,]+")
[docs]class ConllEntry:
def __init__(
self,
eid,
form,
lemma,
pos,
cpos,
feats=None,
parent_id=None,
relation=None,
deps=None,
misc=None,
):
self.id = eid
self.form = form
self.norm = normalize(form)
self.cpos = cpos.upper()
self.pos = pos.upper()
self.parent_id = parent_id
self.relation = relation
self.lemma = lemma
self.feats = feats
self.deps = deps
self.misc = misc
self.pred_parent_id = None
self.pred_relation = None
self.vec = None
self.lstms = None
def __str__(self):
values = [
str(self.id),
self.form,
self.lemma,
self.cpos,
self.pos,
self.feats,
str(self.pred_parent_id) if self.pred_parent_id is not None else None,
self.pred_relation,
self.deps,
self.misc,
]
return "\t".join(["_" if v is None else v for v in values])
[docs]def normalize(word):
return "NUM" if NUMBER_REGEX.match(word) else word.lower()