Update indian_names.py

indian_names.py

@@ -2,7 +2,7 @@ import datasets
 
 logger = datasets.logging.get_logger(__name__)
 
-_URL = "https://raw.githubusercontent.com/Kriyansparsana/demorepo/main/wnut17train%20(1).conll"
+_URL = "https://raw.githubusercontent.com/Kriyansparsana/demorepo/main/train.txt"
 
 class indian_namesConfig(datasets.BuilderConfig):
     """The WNUT 17 Emerging Entities Dataset."""
@@ -23,78 +23,168 @@ class indian_names(datasets.GeneratorBasedBuilder):
         ),
     ]
 
-    def _info(self):
+       def _info(self):
         return datasets.DatasetInfo(
+            description=_DESCRIPTION,
             features=datasets.Features(
                 {
                     "id": datasets.Value("string"),
                     "tokens": datasets.Sequence(datasets.Value("string")),
+                    "pos_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                '"',
+                                "''",
+                                "#",
+                                "$",
+                                "(",
+                                ")",
+                                ",",
+                                ".",
+                                ":",
+                                "``",
+                                "CC",
+                                "CD",
+                                "DT",
+                                "EX",
+                                "FW",
+                                "IN",
+                                "JJ",
+                                "JJR",
+                                "JJS",
+                                "LS",
+                                "MD",
+                                "NN",
+                                "NNP",
+                                "NNPS",
+                                "NNS",
+                                "NN|SYM",
+                                "PDT",
+                                "POS",
+                                "PRP",
+                                "PRP$",
+                                "RB",
+                                "RBR",
+                                "RBS",
+                                "RP",
+                                "SYM",
+                                "TO",
+                                "UH",
+                                "VB",
+                                "VBD",
+                                "VBG",
+                                "VBN",
+                                "VBP",
+                                "VBZ",
+                                "WDT",
+                                "WP",
+                                "WP$",
+                                "WRB",
+                            ]
+                        )
+                    ),
+                    "chunk_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "O",
+                                "B-ADJP",
+                                "I-ADJP",
+                                "B-ADVP",
+                                "I-ADVP",
+                                "B-CONJP",
+                                "I-CONJP",
+                                "B-INTJ",
+                                "I-INTJ",
+                                "B-LST",
+                                "I-LST",
+                                "B-NP",
+                                "I-NP",
+                                "B-PP",
+                                "I-PP",
+                                "B-PRT",
+                                "I-PRT",
+                                "B-SBAR",
+                                "I-SBAR",
+                                "B-UCP",
+                                "I-UCP",
+                                "B-VP",
+                                "I-VP",
+                            ]
+                        )
+                    ),
                     "ner_tags": datasets.Sequence(
                         datasets.features.ClassLabel(
                             names=[
                                 "O",
-                                "B-corporation",
-                                "I-corporation",
-                                "B-person",
-                                "I-person"
+                                "B-PER",
+                                "I-PER",
+                                "B-ORG",
+                                "I-ORG",
+                                "B-LOC",
+                                "I-LOC",
+                                "B-MISC",
+                                "I-MISC",
                             ]
                         )
                     ),
                 }
             ),
             supervised_keys=None,
+            homepage="https://www.aclweb.org/anthology/W03-0419/",
+            citation=_CITATION,
         )
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        urls_to_download = {
-            "train": f"{_URL}",
+        downloaded_file = dl_manager.download_and_extract(_URL)
+        data_files = {
+            "train": os.path.join(downloaded_file, _TRAINING_FILE),
+            "dev": os.path.join(downloaded_file, _DEV_FILE),
+            "test": os.path.join(downloaded_file, _TEST_FILE),
         }
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
 
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}),
         ]
-            
+
     def _generate_examples(self, filepath):
         logger.info("⏳ Generating examples from = %s", filepath)
         with open(filepath, encoding="utf-8") as f:
-            current_tokens = []
-            current_labels = []
-            sentence_counter = 0
-            for row in f:
-                row = row.rstrip()
-                if row:
-                    if "\t" in row:
-                        token, label = row.split("\t")
-                        current_tokens.append(token)
-                        current_labels.append(label)
-                    else:
-                        # Handle cases where the delimiter is missing
-                        # You can choose to skip these rows or handle them differently
-                        logger.warning(f"Delimiter missing in row: {row}")
+            guid = 0
+            tokens = []
+            pos_tags = []
+            chunk_tags = []
+            ner_tags = []
+            for line in f:
+                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
+                    if tokens:
+                        yield guid, {
+                            "id": str(guid),
+                            "tokens": tokens,
+                            "pos_tags": pos_tags,
+                            "chunk_tags": chunk_tags,
+                            "ner_tags": ner_tags,
+                        }
+                        guid += 1
+                        tokens = []
+                        pos_tags = []
+                        chunk_tags = []
+                        ner_tags = []
                 else:
-                    # New sentence
-                    if not current_tokens:
-                        # Consecutive empty lines will cause empty sentences
-                        continue
-                    assert len(current_tokens) == len(current_labels), "💔 between len of tokens & labels"
-                    sentence = (
-                        sentence_counter,
-                        {
-                            "id": str(sentence_counter),
-                            "tokens": current_tokens,
-                            "ner_tags": current_labels,
-                        },
-                    )
-                    sentence_counter += 1
-                    current_tokens = []
-                    current_labels = []
-                    yield sentence
-            # Don't forget the last sentence in the dataset 🧐
-            if current_tokens:
-                yield sentence_counter, {
-                    "id": str(sentence_counter),
-                    "tokens": current_tokens,
-                    "ner_tags": current_labels,
+                    # conll2003 tokens are space separated
+                    splits = line.split(" ")
+                    tokens.append(splits[0])
+                    pos_tags.append(splits[1])
+                    chunk_tags.append(splits[2])
+                    ner_tags.append(splits[3].rstrip())
+            # last example
+            if tokens:
+                yield guid, {
+                    "id": str(guid),
+                    "tokens": tokens,
+                    "pos_tags": pos_tags,
+                    "chunk_tags": chunk_tags,
+                    "ner_tags": ner_tags,
                 }