Datasets:

tomaarsen
/

conllpp

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README.md ADDED Viewed

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
+languages:
+- en
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- extended|conll2003
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+# Dataset Card for "conllpp"
+## Table of Contents
+- [Dataset Card for conllpp](#dataset-card-for-dataset-name)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [Personal and Sensitive Information](#personal-and-sensitive-information)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+  - [Additional Information](#additional-information)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+    - [Contributions](#contributions)
+## Dataset Description
+- **Homepage:** [Github](https://github.com/ZihanWangKi/CrossWeigh)
+- **Repository:** [Github](https://github.com/ZihanWangKi/CrossWeigh)
+- **Paper:** [Aclweb](https://www.aclweb.org/anthology/D19-1519)
+- **Leaderboard:**
+- **Point of Contact:**
+### Dataset Summary
+CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set
+have been manually corrected. The training set and development set from CoNLL2003 is included for completeness. One
+correction on the test set for example, is:
+```
+{
+    "tokens": ["SOCCER", "-", "JAPAN", "GET", "LUCKY", "WIN", ",", "CHINA", "IN", "SURPRISE", "DEFEAT", "."],
+    "original_ner_tags_in_conll2003": ["O", "O", "B-LOC", "O", "O", "O", "O", "B-PER", "O", "O", "O", "O"],
+    "corrected_ner_tags_in_conllpp": ["O", "O", "B-LOC", "O", "O", "O", "O", "B-LOC", "O", "O", "O", "O"],
+}
+```
+### Supported Tasks and Leaderboards
+[More Information Needed]
+### Languages
+[More Information Needed]
+## Dataset Structure
+We show detailed information for up to 5 configurations of the dataset.
+### Data Instances
+#### conllpp
+- **Size of downloaded dataset files:** 4.63 MB
+- **Size of the generated dataset:** 9.78 MB
+- **Total amount of disk used:** 14.41 MB
+An example of 'train' looks as follows.
+```
+This example was too long and was cropped:
+{
+    "chunk_tags": [11, 12, 12, 21, 13, 11, 11, 21, 13, 11, 12, 13, 11, 21, 22, 11, 12, 17, 11, 21, 17, 11, 12, 12, 21, 22, 22, 13, 11, 0],
+    "id": "0",
+    "ner_tags": [0, 3, 4, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+    "pos_tags": [12, 22, 22, 38, 15, 22, 28, 38, 15, 16, 21, 35, 24, 35, 37, 16, 21, 15, 24, 41, 15, 16, 21, 21, 20, 37, 40, 35, 21, 7],
+    "tokens": ["The", "European", "Commission", "said", "on", "Thursday", "it", "disagreed", "with", "German", "advice", "to", "consumers", "to", "shun", "British", "lamb", "until", "scientists", "determine", "whether", "mad", "cow", "disease", "can", "be", "transmitted", "to", "sheep", "."]
+}
+```
+### Data Fields
+The data fields are the same among all splits.
+#### conllpp
+- `id`: a `string` feature.
+- `tokens`: a `list` of `string` features.
+- `pos_tags`: a `list` of classification labels, with possible values including `"` (0), `''` (1), `#` (2), `$` (3), `(` (4).
+- `chunk_tags`: a `list` of classification labels, with possible values including `O` (0), `B-ADJP` (1), `I-ADJP` (2), `B-ADVP` (3), `I-ADVP` (4).
+- `ner_tags`: a `list` of classification labels, with possible values including `O` (0), `B-PER` (1), `I-PER` (2), `B-ORG` (3), `I-ORG` (4).
+### Data Splits Sample Size
+|  name   |train|validation|test|
+|---------|----:|---------:|---:|
+|conll2003|14041|      3250|3453|
+## Dataset Creation
+### Curation Rationale
+[More Information Needed]
+### Source Data
+#### Initial Data Collection and Normalization
+[More Information Needed]
+#### Who are the source language producers?
+[More Information Needed]
+### Annotations
+#### Annotation process
+[More Information Needed]
+#### Who are the annotators?
+[More Information Needed]
+### Personal and Sensitive Information
+[More Information Needed]
+## Considerations for Using the Data
+### Social Impact of Dataset
+[More Information Needed]
+### Discussion of Biases
+[More Information Needed]
+### Other Known Limitations
+[More Information Needed]
+## Additional Information
+### Dataset Curators
+[More Information Needed]
+### Licensing Information
+[More Information Needed]
+### Citation Information
+[More Information Needed]
+### Contributions
+Thanks to [@ZihanWangKi](https://github.com/ZihanWangKi) for adding this dataset.

conllpp.py ADDED Viewed

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+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Lint as: python3
+"""CrossWeigh: Training Named Entity Tagger from Imperfect Annotations"""
+import logging
+import datasets
+_CITATION = """\
+@inproceedings{wang2019crossweigh,
+  title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},
+  author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},
+  booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
+  pages={5157--5166},
+  year={2019}
+}
+"""
+_DESCRIPTION = """\
+CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set
+have been manually corrected. The training set and development set are included for completeness.
+For more details see https://www.aclweb.org/anthology/D19-1519/ and https://github.com/ZihanWangKi/CrossWeigh
+"""
+_URL = "https://github.com/ZihanWangKi/CrossWeigh/raw/master/data/"
+_TRAINING_FILE = "conllpp_train.txt"
+_DEV_FILE = "conllpp_dev.txt"
+_TEST_FILE = "conllpp_test.txt"
+class ConllppConfig(datasets.BuilderConfig):
+    """BuilderConfig for Conll2003"""
+    def __init__(self, **kwargs):
+        """BuilderConfig forConll2003.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(ConllppConfig, self).__init__(**kwargs)
+class Conllpp(datasets.GeneratorBasedBuilder):
+    """Conllpp dataset."""
+    BUILDER_CONFIGS = [
+        ConllppConfig(name="conllpp", version=datasets.Version("1.0.0"), description="Conllpp dataset"),
+    ]
+    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-PER",
+                                "I-PER",
+                                "B-ORG",
+                                "I-ORG",
+                                "B-LOC",
+                                "I-LOC",
+                                "B-MISC",
+                                "I-MISC",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/ZihanWangKi/CrossWeigh",
+            citation=_CITATION,
+        )
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{_TRAINING_FILE}",
+            "dev": f"{_URL}{_DEV_FILE}",
+            "test": f"{_URL}{_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.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+    def _generate_examples(self, filepath):
+        logging.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            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:
+                    # 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,
+                }

dataset_infos.json ADDED Viewed

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+ {"conllpp": {"description": "CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set\nhave been manually corrected. The training set and development set are included for completeness.\nFor more details see https://www.aclweb.org/anthology/D19-1519/ and https://github.com/ZihanWangKi/CrossWeigh\n", "citation": "@inproceedings{wang2019crossweigh,\n title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},\n author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},\n booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},\n pages={5157--5166},\n year={2019}\n}\n", "homepage": "https://github.com/ZihanWangKi/CrossWeigh", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "pos_tags": {"feature": {"num_classes": 47, "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"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "chunk_tags": {"feature": {"num_classes": 23, "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"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 9, "names": ["O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-MISC", "I-MISC"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "conllpp", "config_name": "conllpp", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 6931393, "num_examples": 14041, "dataset_name": "conllpp"}, "validation": {"name": "validation", "num_bytes": 1739247, "num_examples": 3250, "dataset_name": "conllpp"}, "test": {"name": "test", "num_bytes": 1582078, "num_examples": 3453, "dataset_name": "conllpp"}}, "download_checksums": {"https://github.com/ZihanWangKi/CrossWeigh/raw/master/data/conllpp_train.txt": {"num_bytes": 3283420, "checksum": "213953b5522fb7924802d883e50f027b2c6ffb5d4d0e63368ed82909f9b60423"}, "https://github.com/ZihanWangKi/CrossWeigh/raw/master/data/conllpp_dev.txt": {"num_bytes": 827443, "checksum": "c02eb19809eafb83998326a0481942eb37d96f31826ae387cfe8773699969f5b"}, "https://github.com/ZihanWangKi/CrossWeigh/raw/master/data/conllpp_test.txt": {"num_bytes": 748737, "checksum": "4eb3b5114787d0df24087e9c9dfc956abf4cfd5e201bc1056b48ff4f7b37c0e8"}}, "download_size": 4859600, "post_processing_size": null, "dataset_size": 10252718, "size_in_bytes": 15112318}}

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