Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
100K - 1M
Tags:
structure-prediction
License:
fixed https://github.com/huggingface/datasets/issues/2746
Browse files- few-nerd.py +10 -8
few-nerd.py
CHANGED
@@ -21,6 +21,8 @@ and 4,601,223 tokens. Three benchmark tasks are built, one is supervised: Few-NE
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other two are few-shot: Few-NERD (INTRA) and Few-NERD (INTER).
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"""
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# the original data files (zip of .txt) can be downloaded from tsinghua cloud
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_URLs = {
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"supervised": "https://cloud.tsinghua.edu.cn/f/09265750ae6340429827/?dl=1",
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@@ -241,13 +243,13 @@ class FewNERD(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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-
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": os.path.join(
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-
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self.config.name,
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"train.txt",
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)
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@@ -257,7 +259,7 @@ class FewNERD(datasets.GeneratorBasedBuilder):
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": os.path.join(
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-
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)
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},
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),
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@@ -265,7 +267,7 @@ class FewNERD(datasets.GeneratorBasedBuilder):
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": os.path.join(
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-
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)
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},
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),
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@@ -275,10 +277,10 @@ class FewNERD(datasets.GeneratorBasedBuilder):
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# check file type
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assert filepath[-4:] == ".txt"
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-
num_lines = sum(1 for _ in open(filepath))
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id = 0
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-
with open(filepath, "r") as f:
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tokens, ner_tags, fine_ner_tags = [], [], []
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for line in tqdm(f, total=num_lines):
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line = line.strip().split()
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@@ -303,7 +305,7 @@ class FewNERD(datasets.GeneratorBasedBuilder):
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tokens, ner_tags, fine_ner_tags = [], [], []
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id += 1
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yield record["id"], record
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-
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# take the last sentence
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if tokens:
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record = {
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@@ -312,4 +314,4 @@ class FewNERD(datasets.GeneratorBasedBuilder):
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"ner_tags": ner_tags,
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"fine_ner_tags": fine_ner_tags,
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}
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-
yield record["id"], record
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other two are few-shot: Few-NERD (INTRA) and Few-NERD (INTER).
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"""
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+
_LICENSE = "CC BY-SA 4.0"
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+
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# the original data files (zip of .txt) can be downloaded from tsinghua cloud
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_URLs = {
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"supervised": "https://cloud.tsinghua.edu.cn/f/09265750ae6340429827/?dl=1",
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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+
url_to_download = dl_manager.download_and_extract(_URLs[self.config.name])
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": os.path.join(
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+
url_to_download,
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self.config.name,
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"train.txt",
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)
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": os.path.join(
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url_to_download, self.config.name, "dev.txt"
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)
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},
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),
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": os.path.join(
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+
url_to_download, self.config.name, "test.txt"
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)
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},
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),
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# check file type
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assert filepath[-4:] == ".txt"
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+
num_lines = sum(1 for _ in open(filepath, encoding="utf-8"))
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id = 0
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+
with open(filepath, "r", encoding="utf-8") as f:
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tokens, ner_tags, fine_ner_tags = [], [], []
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for line in tqdm(f, total=num_lines):
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line = line.strip().split()
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tokens, ner_tags, fine_ner_tags = [], [], []
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id += 1
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yield record["id"], record
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+
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# take the last sentence
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if tokens:
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record = {
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"ner_tags": ner_tags,
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"fine_ner_tags": fine_ner_tags,
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}
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+
yield record["id"], record
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