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cjvt-valency/dip_src/valency/reduce_functions.py

243 lines
7.4 KiB

# Reduction function for frames.
# Input: list of Frame objects, output: list of Frame objects.
# App uses reduce_0, 1 and 5
from valency.frame import Frame, Slot
from copy import deepcopy as DC
import logging
log = logging.getLogger(__name__)
SENSE_UNDEFINED = "nedefinirano"
## TIDI: use frame.py
## TODO: build a list of [Frame] with lists of [Slot]
def sorted_by_len_tids(frames):
return sorted(
frames,
key=lambda x: len(x.tids),
reverse=True
)
def reduce_0(frames, vallex=None):
# new request... frames should be sorded by
# functors list (basically reduce_1, just each
# sentence gets its own frame)
r1_frames = reduce_1(frames)
sorting_strings = []
separated_frames = []
for frame in r1_frames:
for tid in frame.tids:
tmp_frame = DC(frame)
tmp_frame.tids = [tid]
separated_frames.append(tmp_frame)
sorting_strings.append("".join(
[slot.functor for slot in tmp_frame.slots]
))
permutation = [x for _, x in sorted(
zip(sorting_strings, range(len(sorting_strings))))]
sorted_sep_frames = [separated_frames[i] for i in permutation]
return sorted_sep_frames
def reduce_1(frames, vallex=None):
# Combine frames with the same set of functors.
# The order of functors is not important.
frame_sets = [] # [set of functors, list of frames]
for frame in frames:
functors = [slot.functor for slot in frame.slots]
for fs in frame_sets:
if set(functors) == set(fs[0]):
fs[1].append(frame)
break
else:
# Python for else -> fires if loop has ended.
frame_sets.append([functors, [frame]])
ret_frames = []
for fs in frame_sets:
tids = []
slots = {}
# All possible slots in this frame.
for functor in fs[0]:
slots[functor] = Slot(functor=functor)
# Reduce slots from all frames. (Merge ACT from all frames, ...)
for frame in fs[1]:
tids += frame.tids
for sl in frame.slots:
slots[sl.functor].tids += sl.tids
slots_list = []
for k, e in slots.items():
slots_list.append(e)
rf = Frame(tids=tids, slots=slots_list)
rf.sort_slots()
ret_frames.append(rf)
return sorted_by_len_tids(ret_frames)
def reduce_3(raw_frames, vallex):
# sskj simple lesk ids
ssj_ids = [frame.tids[0] for frame in raw_frames]
db_results = list(vallex.db.sskj_simple_lesk.find(
{"ssj_id": {"$in": ssj_ids}}))
id_map = {}
for entry in db_results:
id_map.update({entry["ssj_id"]: {
"sense_id": entry.get("sense_id"),
"sense_desc": entry.get("sense_desc")
}})
return frames_from_sense_ids(raw_frames, id_map)
def reduce_4(raw_frames, vallex):
# kmeans ids
ssj_ids = [frame.tids[0] for frame in raw_frames]
db_results = list(vallex.db.kmeans.find(
{"ssj_id": {"$in": ssj_ids}}))
id_map = {}
for entry in db_results:
id_map.update({entry["ssj_id"]: {
"sense_id": entry["sense_id"]
}})
return frames_from_sense_ids(raw_frames, id_map)
def reduce_5(raw_frames, vallex):
USER_SENSE_COLL = "v2_sense_map"
headword = raw_frames[0].hw
ssj_ids_full = [frame.tids[0] for frame in raw_frames]
# v2_sense_map stores only sentence half of ssj_id
ssj_ids = [".".join(ssj_id.split(".")[:-1]) for ssj_id in ssj_ids_full]
db_results = list(vallex.db[USER_SENSE_COLL].find({
"ssj_id": {"$in": ssj_ids},
"hw": headword,
}))
id_map = {}
for entry in db_results:
id_map[entry["ssj_id"]] = entry["sense_id"]
ret_frames = frames_from_sense_ids(raw_frames, id_map)
# sort: frames with senses to top
senses_undefined = []
senses_defined = []
for frame in ret_frames:
if frame.sense_info["sense_id"] == SENSE_UNDEFINED:
senses_undefined.append(frame)
else:
senses_defined.append(frame)
ret_frames = senses_defined + senses_undefined
return ret_frames
def frames_from_sense_ids(raw_frames, id_map):
# id map = dict {
# ssj_id: sense_id
# }
# id_dict = dict {
# sense_id: [frame, ...]
# }
id_dict = {}
for frame in raw_frames:
# long version ssj_id (S123.t12)
frame_ssj_id = frame.tids[0]
frame_sense_id = id_map.get(frame_ssj_id)
if frame_sense_id is None:
# try short version ssj_id (S123)
frame_ssj_id = ".".join(frame_ssj_id.split(".")[:-1])
frame_sense_id = id_map.get(frame_ssj_id)
# set default if sense_id not found
if frame_sense_id is None:
frame_sense_id = SENSE_UNDEFINED
"""
sense_id = id_map.get(frame.tids[0])
if sense_id is not None:
sense_id = sense_id.get("sense_id")
else:
sense_id = "nedefinirano"
"""
if frame_sense_id not in id_dict:
id_dict[frame_sense_id] = []
id_dict[frame_sense_id].append(DC(frame))
ret_frames = []
for sense_id, frames in id_dict.items():
tids = []
reduced_slots = []
for frame in frames:
tids.extend(frame.tids)
for slot in frame.slots:
# if functor not in reduced slots,
# add new slot; else increase count
for rslot in reduced_slots:
if slot.functor == rslot.functor:
rslot.count += 1
rslot.tids.extend(slot.tids)
break
else:
# in case for loop didn't match a slot
reduced_slots.append(Slot(
functor=slot.functor,
tids=slot.tids,
count=1
))
reduced_frame = Frame(tids, slots=reduced_slots)
id_map_entry = (
id_map.get(tids[0]) or
id_map.get(".".join(tids[0].split(".")[:-1]))
)
if id_map_entry is None:
reduced_frame.sense_info = {
"sense_id": SENSE_UNDEFINED,
}
else:
reduced_frame.sense_info = {
"sense_id": id_map_entry
}
reduced_frame.sort_slots()
ret_frames.append(reduced_frame)
return ret_frames
reduce_functions = {
"reduce_0": {
"f": reduce_0,
"desc":
"Vsaka pojavitev glagola dobi svoj stavčni vzorec.",
"simple_name": "posamezni stavki"
},
"reduce_1": {
"f": reduce_1,
"desc":
"Združevanje stavčnih vzorcev z enako skupino udeleženskih vlog.",
"simple_name": "združeni stavki"
},
"reduce_3": {
"f": reduce_3,
"desc":
"Združevanje stavčnih vzorcev na osnovi pomenov povedi v SSKJ. "
"Pomeni so dodeljeni s pomočjo algoritma Simple Lesk.",
"simple_name": "SSKJ_pomeni"
},
"reduce_4": {
"f": reduce_4,
"desc":
"Združevanje stavčnih vzorcev na osnovi pomenov povedi "
"s pomočjo algoritma K-Means. Število predvidenih pomenov "
"podano na osnovi SSKJ.",
"simple_name": "KMeans_pomeni"
},
"reduce_5": {
"f": reduce_5,
"desc":
"Uporabniško dodeljeni pomeni povedi.",
"simple_name": "po meri"
}
}