Support 'domains' kwarg in loading

qa_srl2018.py

@@ -16,6 +16,8 @@
 
 
 import datasets
+from dataclasses import dataclass
+from typing import List, Tuple, Union, Set, Iterable
 from pathlib import Path
 import gzip
 import json
@@ -50,21 +52,37 @@ _URLs = {
 
 SpanFeatureType = datasets.Sequence(datasets.Value("int32"), length=2)
 
+SUPPOERTED_DOMAINS = {"wikinews", "wikipedia", "TQA"}
+
+@dataclass
+class QASRL2018BuilderConfig(datasets.BuilderConfig):
+    """ Allow the loader to re-distribute the original dev and test splits between train, dev and test. """    
+    dataset_version: str = "v2_1"
+    
+    domains: Union[str, Iterable[str]] = "all" # can provide also a subset of acceptable domains.
+    # Acceptable domains are {"wikipedia", "wikinews"} for dev and test (qasrl-2020)
+    # and {"wikipedia", "wikinews", "TQA"} for train (qasrl-2018)
+ 
+
 # Name of the dataset usually match the script name with CamelCase instead of snake_case
 class QaSrl2018(datasets.GeneratorBasedBuilder):
     """QA-SRL2018: Large-Scale Question-Answer Driven Semantic Role Labeling corpus"""
 
-    VERSION = datasets.Version("1.0.3")
+    VERSION = datasets.Version("1.2.0")
+
+    BUILDER_CONFIG_CLASS = QASRL2018BuilderConfig
 
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="v2", version=VERSION, description="This provides WIKIPEDIA dataset for qa_srl corpus (original version from Fitzgerald et. al., 2018)"
+        QASRL2018BuilderConfig(
+            name="v2", dataset_version="v2", version=VERSION, 
+            description="This provides WIKIPEDIA dataset for qa_srl corpus (original version from Fitzgerald et. al., 2018)"
         ),
-        datasets.BuilderConfig(
-            name="v2_1", version=VERSION, description="This provides WIKIPEDIA dataset for qa_srl corpus (version 2.1)"
+        QASRL2018BuilderConfig(
+            name="v2_1", dataset_version="v2_1", version=VERSION, 
+            description="This provides WIKIPEDIA dataset for qa_srl corpus (version 2.1)"
         ),
     ]
-
+    
     DEFAULT_CONFIG_NAME = (
         "v2_1"  
     )
@@ -105,12 +123,25 @@ class QaSrl2018(datasets.GeneratorBasedBuilder):
 
         # iterate the tar file of the corpus
                
-        qasrl_dataset_version = self.config_id
+        qasrl_dataset_version = self.config.dataset_version
         corpus_base_path = Path(dl_manager.download_and_extract(_URLs[f"qasrl_{qasrl_dataset_version}"]))
         corpus_orig = corpus_base_path / f"qasrl-{qasrl_dataset_version}" / "orig"
         
+        # Handle domain selection
+        domains: Set[str] = [] 
+        if self.config.domains == "all":
+            domains = SUPPOERTED_DOMAINS
+        elif isinstance(self.config.domains, str):
+            if self.config.domains in SUPPOERTED_DOMAINS:
+                domains = {self.config.domains}
+            else:
+                raise ValueError(f"Unrecognized domain '{self.config.domains}'; only {SUPPOERTED_DOMAINS} are supported")
+        else:
+            domains = set(self.config.domains) & SUPPOERTED_DOMAINS
+            if len(domains) == 0:
+                raise ValueError(f"Unrecognized domains '{self.config.domains}'; only {SUPPOERTED_DOMAINS} are supported")
+        self.config.domains = domains
         
-        # TODO add optional kwarg for genre (wikinews) 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -145,6 +176,11 @@ class QaSrl2018(datasets.GeneratorBasedBuilder):
                 sent_obj = json.loads(line.strip())
                 tokens = sent_obj['sentenceTokens']
                 sentence = ' '.join(tokens)
+                sent_id = sent_obj['sentenceId']
+                # consider only selected domains
+                sent_domain = "TQA" if sent_id.startswith("TQA") else sent_id.split(":")[1]
+                if sent_domain not in self.config.domains:
+                    continue
                 for predicate_idx, verb_obj in sent_obj['verbEntries'].items():
                     verb_forms = verb_obj['verbInflectedForms']
                     predicate = tokens[int(predicate_idx)]
@@ -174,7 +210,7 @@ class QaSrl2018(datasets.GeneratorBasedBuilder):
                         
                         yield qa_counter, {
                             "sentence": sentence,
-                            "sent_id": sent_obj['sentenceId'],
+                            "sent_id": sent_id,
                             "predicate_idx": predicate_idx,
                             "predicate": predicate,
                             "is_verbal": True,