Datasets:
Tasks:
Token Classification
Sub-tasks:
parsing
import glob | |
import logging | |
from dataclasses import dataclass | |
from os import listdir, path | |
from typing import Dict, List, Optional | |
import datasets | |
from datasets import BuilderConfig, DatasetInfo, Features, Sequence, SplitGenerator, Value | |
logger = logging.getLogger(__name__) | |
class BratConfig(BuilderConfig): | |
"""BuilderConfig for BRAT.""" | |
url: str = None # type: ignore | |
description: Optional[str] = None | |
citation: Optional[str] = None | |
homepage: Optional[str] = None | |
subdirectory_mapping: Optional[Dict[str, str]] = None | |
file_name_blacklist: Optional[List[str]] = None | |
ann_file_extension: str = "ann" | |
txt_file_extension: str = "txt" | |
class Brat(datasets.GeneratorBasedBuilder): | |
BUILDER_CONFIG_CLASS = BratConfig | |
def _info(self): | |
return DatasetInfo( | |
description=self.config.description, | |
citation=self.config.citation, | |
homepage=self.config.homepage, | |
features=Features( | |
{ | |
"context": Value("string"), | |
"file_name": Value("string"), | |
"spans": Sequence( | |
{ | |
"id": Value("string"), | |
"type": Value("string"), | |
"locations": Sequence( | |
{ | |
"start": Value("int32"), | |
"end": Value("int32"), | |
} | |
), | |
"text": Value("string"), | |
} | |
), | |
"relations": Sequence( | |
{ | |
"id": Value("string"), | |
"type": Value("string"), | |
"arguments": Sequence( | |
{"type": Value("string"), "target": Value("string")} | |
), | |
} | |
), | |
"equivalence_relations": Sequence( | |
{ | |
"type": Value("string"), | |
"targets": Sequence(Value("string")), | |
} | |
), | |
"events": Sequence( | |
{ | |
"id": Value("string"), | |
"type": Value("string"), | |
"trigger": Value("string"), | |
"arguments": Sequence( | |
{"type": Value("string"), "target": Value("string")} | |
), | |
} | |
), | |
"attributions": Sequence( | |
{ | |
"id": Value("string"), | |
"type": Value("string"), | |
"target": Value("string"), | |
"value": Value("string"), | |
} | |
), | |
"normalizations": Sequence( | |
{ | |
"id": Value("string"), | |
"type": Value("string"), | |
"target": Value("string"), | |
"resource_id": Value("string"), | |
"entity_id": Value("string"), | |
} | |
), | |
"notes": Sequence( | |
{ | |
"id": Value("string"), | |
"type": Value("string"), | |
"target": Value("string"), | |
"note": Value("string"), | |
} | |
), | |
} | |
), | |
) | |
def _get_location(location_string): | |
parts = location_string.split(" ") | |
assert ( | |
len(parts) == 2 | |
), f"Wrong number of entries in location string. Expected 2, but found: {parts}" | |
return {"start": int(parts[0]), "end": int(parts[1])} | |
def _get_span_annotation(annotation_line): | |
""" | |
example input: | |
T1 Organization 0 4 Sony | |
""" | |
_id, remaining, text = annotation_line.split("\t", maxsplit=2) | |
_type, locations = remaining.split(" ", maxsplit=1) | |
return { | |
"id": _id, | |
"text": text, | |
"type": _type, | |
"locations": [Brat._get_location(loc) for loc in locations.split(";")], | |
} | |
def _get_event_annotation(annotation_line): | |
""" | |
example input: | |
E1 MERGE-ORG:T2 Org1:T1 Org2:T3 | |
""" | |
_id, remaining = annotation_line.strip().split("\t") | |
args = [dict(zip(["type", "target"], a.split(":"))) for a in remaining.split(" ")] | |
return { | |
"id": _id, | |
"type": args[0]["type"], | |
"trigger": args[0]["target"], | |
"arguments": args[1:], | |
} | |
def _get_relation_annotation(annotation_line): | |
""" | |
example input: | |
R1 Origin Arg1:T3 Arg2:T4 | |
""" | |
_id, remaining = annotation_line.strip().split("\t") | |
_type, remaining = remaining.split(" ", maxsplit=1) | |
args = [dict(zip(["type", "target"], a.split(":"))) for a in remaining.split(" ")] | |
return {"id": _id, "type": _type, "arguments": args} | |
def _get_equivalence_relation_annotation(annotation_line): | |
""" | |
example input: | |
* Equiv T1 T2 T3 | |
""" | |
_, remaining = annotation_line.strip().split("\t") | |
parts = remaining.split(" ") | |
return {"type": parts[0], "targets": parts[1:]} | |
def _get_attribute_annotation(annotation_line): | |
""" | |
example input (binary: implicit value is True, if present, False otherwise): | |
A1 Negation E1 | |
example input (multi-value: explicit value) | |
A2 Confidence E2 L1 | |
""" | |
_id, remaining = annotation_line.strip().split("\t", maxsplit=1) | |
parts = remaining.split() | |
# if no value is present, it is implicitly "true" | |
if len(parts) == 2: | |
parts.append("true") | |
return { | |
"id": _id, | |
"type": parts[0], | |
"target": parts[1], | |
"value": parts[2], | |
} | |
def _get_normalization_annotation(annotation_line): | |
""" | |
example input: | |
N1 Reference T1 Wikipedia:534366 Barack Obama | |
""" | |
_id, remaining, text = annotation_line.split("\t", maxsplit=2) | |
_type, target, ref = remaining.split(" ") | |
res_id, ent_id = ref.split(":") | |
return { | |
"id": _id, | |
"type": _type, | |
"target": target, | |
"resource_id": res_id, | |
"entity_id": ent_id, | |
} | |
def _get_note_annotation(annotation_line): | |
""" | |
example input: | |
#1 AnnotatorNotes T1 this annotation is suspect | |
""" | |
_id, remaining, note = annotation_line.split("\t", maxsplit=2) | |
_type, target = remaining.split(" ") | |
return { | |
"id": _id, | |
"type": _type, | |
"target": target, | |
"note": note, | |
} | |
def _read_annotation_file(filename): | |
""" | |
reads a BRAT v1.3 annotations file (see https://brat.nlplab.org/standoff.html) | |
""" | |
res = { | |
"spans": [], | |
"events": [], | |
"relations": [], | |
"equivalence_relations": [], | |
"attributions": [], | |
"normalizations": [], | |
"notes": [], | |
} | |
with open(filename) as file: | |
for i, line in enumerate(file): | |
if len(line.strip()) == 0: | |
continue | |
ann_type = line[0] | |
# strip away the new line character | |
if line.endswith("\n"): | |
line = line[:-1] | |
if ann_type == "T": | |
res["spans"].append(Brat._get_span_annotation(line)) | |
elif ann_type == "E": | |
res["events"].append(Brat._get_event_annotation(line)) | |
elif ann_type == "R": | |
res["relations"].append(Brat._get_relation_annotation(line)) | |
elif ann_type == "*": | |
res["equivalence_relations"].append( | |
Brat._get_equivalence_relation_annotation(line) | |
) | |
elif ann_type in ["A", "M"]: | |
res["attributions"].append(Brat._get_attribute_annotation(line)) | |
elif ann_type == "N": | |
res["normalizations"].append(Brat._get_normalization_annotation(line)) | |
elif ann_type == "#": | |
res["notes"].append(Brat._get_note_annotation(line)) | |
else: | |
raise ValueError( | |
f'unknown BRAT annotation id type: "{line}" (from file {filename} @line {i}). ' | |
f"Annotation ids have to start with T (spans), E (events), R (relations), " | |
f"A (attributions), or N (normalizations). See " | |
f"https://brat.nlplab.org/standoff.html for the BRAT annotation file " | |
f"specification." | |
) | |
return res | |
def _generate_examples(self, files=None, directory=None): | |
"""Read context (.txt) and annotation (.ann) files.""" | |
if files is None: | |
assert ( | |
directory is not None | |
), "If files is None, directory has to be provided, but it is also None." | |
_files = glob.glob(f"{directory}/*.{self.config.ann_file_extension}") | |
files = sorted(path.splitext(fn)[0] for fn in _files) | |
for filename in files: | |
basename = path.basename(filename) | |
if ( | |
self.config.file_name_blacklist is not None | |
and basename in self.config.file_name_blacklist | |
): | |
logger.info(f"skip annotation file: {basename} (blacklisted)") | |
continue | |
ann_fn = f"{filename}.{self.config.ann_file_extension}" | |
brat_annotations = Brat._read_annotation_file(ann_fn) | |
txt_fn = f"{filename}.{self.config.txt_file_extension}" | |
txt_content = open(txt_fn).read() | |
brat_annotations["context"] = txt_content | |
brat_annotations["file_name"] = basename | |
yield basename, brat_annotations | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
if self.config.data_dir is not None: | |
data_dir = self.config.data_dir | |
logging.warning(f"load from data_dir: {data_dir}") | |
else: | |
# since subclasses of BuilderConfig are not allowed to define | |
# attributes without defaults, check here | |
assert self.config.url is not None, "data url not specified" | |
data_dir = dl_manager.download_and_extract(self.config.url) | |
subdirectory_mapping = self.config.subdirectory_mapping | |
# if no subdirectory mapping is provided, ... | |
if subdirectory_mapping is None: | |
# ... use available subdirectories as split names ... | |
subdirs = [f for f in listdir(data_dir) if path.isdir(path.join(data_dir, f))] | |
if len(subdirs) > 0: | |
subdirectory_mapping = {subdir: subdir for subdir in subdirs} | |
else: | |
# ... otherwise, default to a single train split with the base directory | |
subdirectory_mapping = {"": "train"} | |
return [ | |
SplitGenerator( | |
name=split, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"directory": path.join(data_dir, subdir), | |
}, | |
) | |
for subdir, split in subdirectory_mapping.items() | |
] |