Update files from the datasets library (from 1.3.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.3.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
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+*.pt filter=lfs diff=lfs merge=lfs -text
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+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+*.tgz filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- crowdsourced
+languages:
+- en
+licenses:
+- cc-by-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- sequence-modeling
+- structure-prediction
+task_ids:
+- coreference-resolution
+- dialogue-modeling
+---
+
+# Dataset Card for IRC Disentanglement
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [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:** https://jkk.name/irc-disentanglement/
+- **Repository:** https://github.com/jkkummerfeld/irc-disentanglement/tree/master/data
+- **Paper:** https://aclweb.org/anthology/papers/P/P19/P19-1374/
+- **Leaderboard:** NA
+- **Point of Contact:** jkummerf@umich.edu
+
+### Dataset Summary
+
+Disentangling conversations mixed together in a single stream of messages is a difficult task, made harder by the lack of large manually annotated datasets. This new dataset of 77,563 messages manually annotated with reply-structure graphs that both disentangle conversations and define internal conversation structure. The dataset is 16 times larger than all previously released datasets combined, the first to include adjudication of annotation disagreements, and the first to include context.
+
+### Supported Tasks and Leaderboards
+
+Conversational Disentanglement, Coreference Resolution, Dialogue Modeling
+
+### Languages
+
+English (en)
+
+## Dataset Structure
+
+### Data Instances
+
+For Ubuntu:
+
+data["train"][1050]
+
+```
+{
+
+  'ascii': "[03:57] <Xophe> (also, I'm guessing that this isn't a good place to report minor but annoying bugs... what is?)", 
+
+  'connections': [1048, 1054, 1055, 1072, 1073], 
+
+  'date': '2004-12-25', 
+
+  'id': 1050,
+
+  'raw': "[03:57] <Xophe> (also, I'm guessing that this isn't a good place to report minor but annoying bugs... what is?)", 
+
+  'tokenized': "<s> ( also , i 'm guessing that this is n't a good place to report minor but annoying bugs ... what is ?) </s>"
+
+}
+```
+
+For Channel_two:
+
+data["train"][50]
+
+```
+{
+
+  'ascii': "[01:04] <Felicia> Chanel: i don't know off hand sorry", 
+
+  'connections': [49, 53], 
+
+  'id': 50,
+
+  'raw': "[01:04] <Felicia> Chanel: i don't know off hand sorry", 
+
+  'tokenized': "<s> <user> : i do n't know off hand sorry </s>"
+
+}
+```
+
+### Data Fields
+
+'id' : The id of the message, this is the value that would be in the 'connections' of associated messages.
+
+'raw' : The original message from the IRC log, as downloaded.
+
+'ascii' : The raw message converted to ascii (unconvertable characters are replaced with a special word).
+
+'tokenized' : The same message with automatic tokenisation and replacement of rare words with placeholder symbols.
+
+'connections' : The indices of linked messages.
+
+(only ubuntu) 'date' : The date the messages are from. The labelling for each date only start after the first 1000 messages of that date.
+
+### Data Splits
+
+ubuntu: This data split is a new dataset introduced by the authors which labels connected messages in an online chatroom about ubuntu.
+
+channel_two: This data split is a re-analysis of prior work on IRC-Disentanglement where issues about the previous data are resolved. The previous dataset is outlined in https://www.aclweb.org/anthology/P08-1095.pdf.
+
+## 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
+
+Jonathan K. Kummerfeld, Sai R. Gouravajhala, Joseph Peper, Vignesh Athreya, Chulaka Gunasekara, Jatin Ganhotra, Siva Sankalp Patel, Lazaros Polymenakos, and Walter S. Lasecki
+
+### Licensing Information
+
+Creative Commons Attribution 4.0
+
+### Citation Information
+
+@InProceedings{acl19disentangle,
+  author    = {Jonathan K. Kummerfeld and Sai R. Gouravajhala and Joseph Peper and Vignesh Athreya and Chulaka Gunasekara and Jatin Ganhotra and Siva Sankalp Patel and Lazaros Polymenakos and Walter S. Lasecki},
+  title     = {A Large-Scale Corpus for Conversation Disentanglement},
+  booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
+  location  = {Florence, Italy},
+  month     = {July},
+  year      = {2019},
+  doi       = {10.18653/v1/P19-1374},
+  pages     = {3846--3856},
+  url       = {https://aclweb.org/anthology/papers/P/P19/P19-1374/},
+  arxiv     = {https://arxiv.org/abs/1810.11118},
+  software  = {https://jkk.name/irc-disentanglement},
+  data      = {https://jkk.name/irc-disentanglement},
+}
+
+### Contributions
+
+Thanks to [@dhruvjoshi1998](https://github.com/dhruvjoshi1998) for adding this dataset.

dataset_infos.json

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+{"ubuntu": {"description": "Disentangling conversations mixed together in a single stream of messages is\na difficult task, made harder by the lack of large manually annotated\ndatasets. This new dataset of 77,563 messages manually annotated with\nreply-structure graphs that both disentangle conversations and define\ninternal conversation structure. The dataset is 16 times larger than all\npreviously released datasets combined, the first to include adjudication of\nannotation disagreements, and the first to include context.\n", "citation": "@InProceedings{acl19disentangle,\nauthor    = {Jonathan K. Kummerfeld and Sai R. Gouravajhala and Joseph Peper and Vignesh Athreya and Chulaka Gunasekara and Jatin Ganhotra and Siva Sankalp Patel and Lazaros Polymenakos and Walter S. Lasecki},\ntitle     = {A Large-Scale Corpus for Conversation Disentanglement},\nbooktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},\nlocation  = {Florence, Italy},\nmonth     = {July},\nyear      = {2019},\ndoi       = {10.18653/v1/P19-1374},\npages     = {3846--3856},\nurl       = {https://aclweb.org/anthology/papers/P/P19/P19-1374/},\narxiv     = {https://arxiv.org/abs/1810.11118},\nsoftware  = {https://jkk.name/irc-disentanglement},\ndata      = {https://jkk.name/irc-disentanglement},\n}\n", "homepage": "https://jkk.name/irc-disentanglement/", "license": "Creative Commons Attribution 4.0 International Public License", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "raw": {"dtype": "string", "id": null, "_type": "Value"}, "ascii": {"dtype": "string", "id": null, "_type": "Value"}, "tokenized": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}, "connections": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "irc_disentangle", "config_name": "ubuntu", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 55970472, "num_examples": 220616, "dataset_name": "irc_disentangle"}, "test": {"name": "test", "num_bytes": 3916881, "num_examples": 15010, "dataset_name": "irc_disentangle"}, "validation": {"name": "validation", "num_bytes": 3079360, "num_examples": 12510, "dataset_name": "irc_disentangle"}}, "download_checksums": {"https://github.com/jkkummerfeld/irc-disentanglement/tarball/master": {"num_bytes": 118470349, "checksum": "9e2c98a15191d729c0dbe10f309d836bd1ab32c0d03ffb2e0e4205287405fc4d"}}, "download_size": 118470349, "post_processing_size": null, "dataset_size": 62966713, "size_in_bytes": 181437062}, "channel_two": {"description": "Disentangling conversations mixed together in a single stream of messages is\na difficult task, made harder by the lack of large manually annotated\ndatasets. This new dataset of 77,563 messages manually annotated with\nreply-structure graphs that both disentangle conversations and define\ninternal conversation structure. The dataset is 16 times larger than all\npreviously released datasets combined, the first to include adjudication of\nannotation disagreements, and the first to include context.\n", "citation": "@InProceedings{acl19disentangle,\nauthor    = {Jonathan K. Kummerfeld and Sai R. Gouravajhala and Joseph Peper and Vignesh Athreya and Chulaka Gunasekara and Jatin Ganhotra and Siva Sankalp Patel and Lazaros Polymenakos and Walter S. Lasecki},\ntitle     = {A Large-Scale Corpus for Conversation Disentanglement},\nbooktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},\nlocation  = {Florence, Italy},\nmonth     = {July},\nyear      = {2019},\ndoi       = {10.18653/v1/P19-1374},\npages     = {3846--3856},\nurl       = {https://aclweb.org/anthology/papers/P/P19/P19-1374/},\narxiv     = {https://arxiv.org/abs/1810.11118},\nsoftware  = {https://jkk.name/irc-disentanglement},\ndata      = {https://jkk.name/irc-disentanglement},\n}\n", "homepage": "https://jkk.name/irc-disentanglement/", "license": "Creative Commons Attribution 4.0 International Public License", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "raw": {"dtype": "string", "id": null, "_type": "Value"}, "ascii": {"dtype": "string", "id": null, "_type": "Value"}, "tokenized": {"dtype": "string", "id": null, "_type": "Value"}, "connections": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "irc_disentangle", "config_name": "channel_two", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"dev": {"name": "dev", "num_bytes": 197189, "num_examples": 1001, "dataset_name": "irc_disentangle"}, "pilot": {"name": "pilot", "num_bytes": 92514, "num_examples": 501, "dataset_name": "irc_disentangle"}, "test": {"name": "test", "num_bytes": 186494, "num_examples": 1001, "dataset_name": "irc_disentangle"}, "pilot_dev": {"name": "pilot_dev", "num_bytes": 289695, "num_examples": 1501, "dataset_name": "irc_disentangle"}, "all_": {"name": "all_", "num_bytes": 495666, "num_examples": 2602, "dataset_name": "irc_disentangle"}}, "download_checksums": {"https://github.com/jkkummerfeld/irc-disentanglement/tarball/master": {"num_bytes": 118470349, "checksum": "9e2c98a15191d729c0dbe10f309d836bd1ab32c0d03ffb2e0e4205287405fc4d"}}, "download_size": 118470349, "post_processing_size": null, "dataset_size": 1261558, "size_in_bytes": 119731907}}

dummy/channel_two/1.0.0/dummy_data.zip

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dummy/ubuntu/1.0.0/dummy_data.zip

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irc_disentangle.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+"""Dataset of disentangled IRC"""
+
+from __future__ import absolute_import, division, print_function
+
+import glob
+import os
+from pathlib import Path
+
+import datasets
+
+
+_CITATION = """\
+@InProceedings{acl19disentangle,
+author    = {Jonathan K. Kummerfeld and Sai R. Gouravajhala and Joseph Peper and Vignesh Athreya and Chulaka Gunasekara and Jatin Ganhotra and Siva Sankalp Patel and Lazaros Polymenakos and Walter S. Lasecki},
+title     = {A Large-Scale Corpus for Conversation Disentanglement},
+booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
+location  = {Florence, Italy},
+month     = {July},
+year      = {2019},
+doi       = {10.18653/v1/P19-1374},
+pages     = {3846--3856},
+url       = {https://aclweb.org/anthology/papers/P/P19/P19-1374/},
+arxiv     = {https://arxiv.org/abs/1810.11118},
+software  = {https://jkk.name/irc-disentanglement},
+data      = {https://jkk.name/irc-disentanglement},
+}
+"""
+
+_DESCRIPTION = """\
+Disentangling conversations mixed together in a single stream of messages is
+a difficult task, made harder by the lack of large manually annotated
+datasets. This new dataset of 77,563 messages manually annotated with
+reply-structure graphs that both disentangle conversations and define
+internal conversation structure. The dataset is 16 times larger than all
+previously released datasets combined, the first to include adjudication of
+annotation disagreements, and the first to include context.
+"""
+
+_HOMEPAGE = "https://jkk.name/irc-disentanglement/"
+
+_LICENSE = "Creative Commons Attribution 4.0 International Public License"
+
+_URL = "https://github.com/jkkummerfeld/irc-disentanglement/tarball/master"
+
+
+class IRCDisentangle(datasets.GeneratorBasedBuilder):
+    """IRCDisentangle dataset"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="ubuntu",
+            version=VERSION,
+            description="This part of the dataset is the annotated conversations from the Ubuntu channel",
+        ),
+        datasets.BuilderConfig(
+            name="channel_two",
+            version=VERSION,
+            description="This part of the dataset is the annotated conversations from the Channel Two",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "ubuntu"
+
+    def _info(self):
+        if self.config.name == "ubuntu":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "raw": datasets.Value("string"),
+                    "ascii": datasets.Value("string"),
+                    "tokenized": datasets.Value("string"),
+                    "date": datasets.Value("string"),
+                    "connections": datasets.features.Sequence(datasets.Value("int32")),
+                }
+            )
+        elif self.config.name == "channel_two":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "raw": datasets.Value("string"),
+                    "ascii": datasets.Value("string"),
+                    "tokenized": datasets.Value("string"),
+                    "connections": datasets.features.Sequence(datasets.Value("int32")),
+                }
+            )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        my_urls = _URL
+        dl_dir = dl_manager.download_and_extract(my_urls)
+
+        files = dict()
+        if self.config.name == "ubuntu":
+            for split in ["train", "dev", "test"]:
+                files[split] = os.path.join(dl_dir, "jkkummerfeld-irc-disentanglement-fd379e9", "data", split)
+
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "filepath": files["train"],
+                        "split": "train",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "filepath": files["test"],
+                        "split": "test",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    gen_kwargs={
+                        "filepath": files["dev"],
+                        "split": "dev",
+                    },
+                ),
+            ]
+
+        elif self.config.name == "channel_two":
+            filepath = os.path.join(dl_dir, "jkkummerfeld-irc-disentanglement-fd379e9", "data", "channel-two")
+            return [
+                datasets.SplitGenerator(
+                    name="dev",
+                    gen_kwargs={
+                        "filepath": filepath,
+                        "split": "dev",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="pilot",
+                    gen_kwargs={
+                        "filepath": filepath,
+                        "split": "pilot",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="test",
+                    gen_kwargs={
+                        "filepath": filepath,
+                        "split": "test",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="pilot_dev",
+                    gen_kwargs={
+                        "filepath": filepath,
+                        "split": "pilot-dev",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="all_",
+                    gen_kwargs={
+                        "filepath": filepath,
+                        "split": "all",
+                    },
+                ),
+            ]
+
+    def _generate_examples(self, filepath, split):
+        """ Yields examples. """
+
+        if self.config.name == "ubuntu":
+            # run loop for each date
+            all_files = sorted(glob.glob(os.path.join(filepath, "*.annotation.txt")))
+            all_dates = [Path(file).name[:10] for file in all_files]
+            all_info = [Path(file).name[10:-15] for file in all_files]
+
+        elif self.config.name == "channel_two":
+            # run loop once (there are no dates for this config)
+            all_dates = ["_"]
+            all_info = ["_"]
+
+        last_id = 0
+        id_ = 0
+
+        for date, info in zip(all_dates, all_info):
+
+            if self.config.name == "ubuntu":
+                # load file of given date and additional info for each split
+                raw_path = os.path.join(filepath, f"{date}{info}.raw.txt")
+                ascii_path = os.path.join(filepath, f"{date}{info}.ascii.txt")
+                tok_path = os.path.join(filepath, f"{date}{info}.tok.txt")
+                annot_path = os.path.join(filepath, f"{date}{info}.annotation.txt")
+
+            elif self.config.name == "channel_two":
+                # load files of different splits
+                raw_path = os.path.join(filepath, f"channel-two.{split}.raw.txt")
+                ascii_path = os.path.join(filepath, f"channel-two.{split}.ascii.txt")
+                tok_path = os.path.join(filepath, f"channel-two.{split}.tok.txt")
+                annot_path = os.path.join(filepath, f"channel-two.{split}.annotation.txt")
+
+            with open(raw_path, encoding="utf-8") as f_raw, open(ascii_path, encoding="utf-8") as f_ascii, open(
+                tok_path, encoding="utf-8"
+            ) as f_tok, open(annot_path, encoding="utf-8") as f_annot:
+
+                # tokenize txt file
+                raw_sentences = f_raw.read().split("\n")
+                ascii_sentences = f_ascii.read().split("\n")
+                tok_sentences = f_tok.read().split("\n")
+                annot_lines = f_annot.read().split("\n")
+
+            assert (
+                len(raw_sentences) == len(ascii_sentences) == len(tok_sentences)
+            ), "Sizes do not match: %d vs %d vs %d for Raw Sentences vs Ascii Sentences vs Tokenized Sentences." % (
+                len(raw_sentences),
+                len(ascii_sentences),
+                len(tok_sentences),
+            )
+
+            annotation_pairs = []
+
+            # for annotation lines, make annotation pairs
+            for annot in annot_lines:
+                line = annot.split(" ")
+                if len(line) > 1:
+                    annotation_pairs.append((int(line[0]), int(line[1])))
+
+            annotations = dict()
+            for row in range(last_id, last_id + len(raw_sentences)):
+                annotations[row] = set()
+
+            for (a, b) in annotation_pairs:
+                # required for dummy data creation
+                if last_id + a not in annotations:
+                    annotations[last_id + a] = set()
+                if last_id + b not in annotations:
+                    annotations[last_id + b] = set()
+
+                # add annotation 'b' to a's annotation set, and vice versa
+                annotations[last_id + a].add(last_id + b)
+                annotations[last_id + b].add(last_id + a)
+
+            for i in range(len(raw_sentences)):
+                # return all 3 kinds of chat messages, the date (if applicable), and the annotation set for that sentece
+                if self.config.name == "ubuntu":
+                    yield id_, {
+                        "id": id_,
+                        "raw": raw_sentences[i],
+                        "ascii": ascii_sentences[i],
+                        "tokenized": tok_sentences[i],
+                        "date": date,
+                        "connections": sorted(annotations[id_]),
+                    }
+                elif self.config.name == "channel_two":
+                    yield id_, {
+                        "id": id_,
+                        "raw": raw_sentences[i],
+                        "ascii": ascii_sentences[i],
+                        "tokenized": tok_sentences[i],
+                        "connections": sorted(annotations[i]),
+                    }
+                id_ += 1
+
+            # continue counting from position last left off
+            last_id = id_