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import json
import logging
import random
from typing import *
import numpy as np
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.fields import MetadataField
from allennlp.data.instance import Instance
from .span_reader import SpanReader
from ..utils import Span, VIRTUAL_ROOT, BIOSmoothing
logger = logging.getLogger(__name__)
@DatasetReader.register('semantic_role_labeling')
class SRLDatasetReader(SpanReader):
def __init__(
self,
min_negative: int = 5,
negative_ratio: float = 1.,
event_only: bool = False,
event_smoothing_factor: float = 0.,
arg_smoothing_factor: float = 0.,
# For Ontology Mapping
ontology_mapping_path: Optional[str] = None,
min_weight: float = 1e-2,
max_weight: float = 1.0,
**extra
):
super().__init__(**extra)
self.min_negative = min_negative
self.negative_ratio = negative_ratio
self.event_only = event_only
self.event_smooth_factor = event_smoothing_factor
self.arg_smooth_factor = arg_smoothing_factor
self.ontology_mapping = None
if ontology_mapping_path is not None:
self.ontology_mapping = json.load(open(ontology_mapping_path))
for k1 in ['event', 'argument']:
for k2, weights in self.ontology_mapping['mapping'][k1].items():
weights = np.array(weights)
weights[weights < min_weight] = 0.0
weights[weights > max_weight] = max_weight
self.ontology_mapping['mapping'][k1][k2] = weights
self.ontology_mapping['mapping'][k1] = {
k2: weights for k2, weights in self.ontology_mapping['mapping'][k1].items() if weights.sum() > 1e-5
}
vr_label = [0.] * len(self.ontology_mapping['target']['label'])
vr_label[self.ontology_mapping['target']['label'].index(VIRTUAL_ROOT)] = 1.0
self.ontology_mapping['mapping']['event'][VIRTUAL_ROOT] = np.array(vr_label)
def _read(self, file_path: str) -> Iterable[Instance]:
all_lines = list(map(json.loads, open(file_path).readlines()))
if self.debug:
random.seed(1); random.shuffle(all_lines)
for line in all_lines:
ins = self.text_to_instance(**line)
if ins is not None:
yield ins
if self.n_span_removed > 0:
logger.warning(f'{self.n_span_removed} spans are removed.')
self.n_span_removed = 0
def apply_ontology_mapping(self, vr):
new_events = list()
event_map, arg_map = self.ontology_mapping['mapping']['event'], self.ontology_mapping['mapping']['argument']
for event in vr:
if event.label not in event_map: continue
event.child_smooth.weight = event.smooth_weight = event_map[event.label].sum()
event = event.map_ontology(event_map, False, False)
new_events.append(event)
new_children = list()
for child in event:
if child.label not in arg_map: continue
child.child_smooth.weight = child.smooth_weight = arg_map[child.label].sum()
child = child.map_ontology(arg_map, False, False)
new_children.append(child)
event.remove_child()
for child in new_children: event.add_child(child)
new_vr = Span.virtual_root(new_events)
# For Virtual Root itself.
new_vr.map_ontology(self.ontology_mapping['mapping']['event'], True, False)
return new_vr
def text_to_instance(self, tokens, annotations=None, meta=None) -> Optional[Instance]:
meta = meta or {'fully_annotated': True}
meta['fully_annotated'] = meta.get('fully_annotated', True)
vr = None
if annotations is not None:
vr = annotations if isinstance(annotations, Span) else Span.from_json(annotations)
vr = self.apply_ontology_mapping(vr) if self.ontology_mapping is not None else vr
# if len(vr) == 0: return # Ignore sentence with empty annotation
if self.event_smooth_factor != 0.0:
vr.child_smooth = BIOSmoothing(o_smooth=self.event_smooth_factor if meta['fully_annotated'] else -1)
if self.arg_smooth_factor != 0.0:
for event in vr:
event.child_smooth = BIOSmoothing(o_smooth=self.arg_smooth_factor)
if self.event_only:
for event in vr:
event.remove_child()
event.is_parent = False
fields = self.prepare_inputs(tokens, vr, True, 'string' if self.ontology_mapping is None else 'list')
fields['meta'] = MetadataField(meta)
return Instance(fields)
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