def load_hardware_labels(
session, candidate_class, filename, attrib, annotator_name="gold"
):
ak = session.query(GoldLabelKey).filter(GoldLabelKey.name == annotator_name).first()
if ak is None:
ak = GoldLabelKey(name=annotator_name)
session.add(ak)
session.commit()
candidates = session.query(candidate_class).all()
gold_dict = get_gold_dict(filename, attribute=attrib)
cand_total = len(candidates)
logger.info("Loading {} candidate labels".format(cand_total))
labels = []
for i, c in enumerate(tqdm(candidates)):
doc = (c[0].span.sentence.document.name).upper()
part = (c[0].span.get_span()).upper()
val = ("".join(c[1].span.get_span().split())).upper()
label = (
session.query(GoldLabel)
.filter(GoldLabel.key == ak)
.filter(GoldLabel.candidate == c)
.first()
)
if label is None:
if (doc, part, val) in gold_dict:
label = GoldLabel(candidate=c, key=ak, value=1)
else:
label = GoldLabel(candidate=c, key=ak, value=-1)
session.add(label)
labels.append(label)
session.commit()
session.commit()
logger.info("AnnotatorLabels created: %s" % (len(labels),))
def load_hardware_labels(
session, candidate_classes, filename, attrib, annotator_name="gold"
):
"""Bulk insert hardware GoldLabels.
:param session: The database session to use.
:param candidate_classes: Which candidate_classes to load labels for.
:param filename: Path to the CSV file containing gold labels.
:param attrib: Which attributes to load labels for (e.g. "stg_temp_max").
"""
# Check that candidate_classes is iterable
candidate_classes = (
candidate_classes
if isinstance(candidate_classes, (list, tuple))
else [candidate_classes]
)
ak = session.query(GoldLabelKey).filter(GoldLabelKey.name == annotator_name).first()
# Add the gold key
if ak is None:
ak = GoldLabelKey(
name=annotator_name,
candidate_classes=[_.__tablename__ for _ in candidate_classes],
)
session.add(ak)
session.commit()
# Bulk insert candidate labels
candidates = []
for candidate_class in candidate_classes:
candidates.extend(session.query(candidate_class).all())
gold_dict = get_gold_dict(filename, attribute=attrib)
cand_total = len(candidates)
logger.info(f"Loading {cand_total} candidate labels")
labels = 0
cands = []
values = []
for i, c in enumerate(tqdm(candidates)):
doc = (c[0].context.sentence.document.name).upper()
part = (c[0].context.get_span()).upper()
val = ("".join(c[1].context.get_span().split())).upper()
label = session.query(GoldLabel).filter(GoldLabel.candidate == c).first()
if label is None:
if (doc, part, val) in gold_dict:
values.append(TRUE)
else:
values.append(FALSE)
cands.append(c)
labels += 1
# Only insert the labels which were not already present
session.bulk_insert_mappings(
GoldLabel,
[
{"candidate_id": cand.id, "keys": [annotator_name], "values": [val]}
for (cand, val) in zip(cands, values)
],
)
session.commit()
logger.info(f"GoldLabels created: {labels}")
def load_president_gold_labels(session,
candidate_classes,
filename,
annotator_name="gold"):
"""Bulk insert hardware GoldLabels.
:param session: The database session to use.
:param candidate_classes: Which candidate_classes to load labels for.
:param filename: Path to the CSV file containing gold labels.
"""
# Check that candidate_classes is iterable
candidate_classes = (candidate_classes if isinstance(
candidate_classes, (list, tuple)) else [candidate_classes])
print("Clearing ALL Gold labels")
session.query(GoldLabel).delete()
session.query(GoldLabelKey).delete()
ak = session.query(GoldLabelKey).filter(
GoldLabelKey.name == annotator_name).first()
# Add the gold key
if ak is None:
ak = GoldLabelKey(
name=annotator_name,
candidate_classes=[_.__tablename__ for _ in candidate_classes],
)
session.add(ak)
session.commit()
# Bulk insert candidate labels
candidates = []
for candidate_class in candidate_classes:
candidates.extend(session.query(candidate_class).all())
gold_dict = get_gold_dict(filename)
cand_total = len(candidates)
print(f"Loading {cand_total} candidate labels")
labels = 0
docs_in_gold_dict = set([x[0] for x in gold_dict])
print(f"{len(docs_in_gold_dict)} different docs in gold dict")
candidates_by_doc = dict()
for name, place in candidates:
doc = name.context.sentence.document.name
if doc not in candidates_by_doc:
candidates_by_doc[doc] = {name: [place]}
else:
if name not in candidates_by_doc[doc]:
candidates_by_doc[doc][name] = [place]
else:
candidates_by_doc[doc][name].append(place)
cands = []
values = []
for i, c in enumerate(tqdm(candidates)):
doc = (c[0].context.sentence.document.name).upper()
president_name = (c[0].context.get_span()).upper()
birthplace = (c[1].context.get_span()).upper()
cand_tuple = (doc, president_name, birthplace)
# gold_matches = [x for x in gold_dict if x[0] == doc]
if cand_tuple in gold_dict:
values.append(TRUE)
else:
values.append(FALSE)
cands.append(c)
labels += 1
# Only insert the labels which were not already present
session.bulk_insert_mappings(
GoldLabel,
[{
"candidate_id": cand.id,
"keys": [annotator_name],
"values": [val]
} for (cand, val) in zip(cands, values)],
)
session.commit()
print(f"GoldLabels created: {labels}")
def load_section_heading_gold_labels(
featurizer_output,annotator_name="gold"
):
"""
:param session: The database session to use.
:param candidate_classes: Which candidate_classes to load labels for.
:param filename: Path to the CSV file containing gold labels.
"""
session = featurizer_output['session']
candidate_classes = featurizer_output['candidate_variable']
filename = config.gold_file_path
# Check that candidate_classes is iterable
candidate_classes = (
candidate_classes
if isinstance(candidate_classes, (list, tuple))
else [candidate_classes]
)
ak = session.query(GoldLabelKey).filter(GoldLabelKey.name == annotator_name).first()
# Add the gold key
if ak is None:
ak = GoldLabelKey(
name=annotator_name,
candidate_classes=[_.__tablename__ for _ in candidate_classes],
)
session.add(ak)
session.commit()
# Bulk insert candidate labels
candidates = []
for candidate_class in candidate_classes:
candidates.extend(session.query(candidate_class).all())
gold_dict = get_gold_dict(filename)
cand_total = len(candidates)
print(f"Loading {cand_total} candidate labels")
labels = 0
cands = []
values = []
for i, c in enumerate(tqdm(candidates)):
doc = (c[0].context.sentence.document.name)
val = (c[0].context.get_span())
label = session.query(GoldLabel).filter(GoldLabel.candidate == c).first()
if label is None:
if (doc, val) in gold_dict:
values.append(TRUE)
else:
values.append(FALSE)
cands.append(c)
labels += 1
# Only insert the labels which were not already present
session.bulk_insert_mappings(
GoldLabel,
[
{"candidate_id": cand.id, "keys": [annotator_name], "values": [val]}
for (cand, val) in zip(cands, values)
],
)
session.commit()
print(f"GoldLabels created: {labels}")