Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K<n<100K
License:
fhamborg
commited on
Commit
•
7ae8760
1
Parent(s):
6726b01
Rename to NewsSentimentNewsmtsc
Browse files
dataset_info.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"rw": {"description": "NewsMTSC: A large, manually annotated dataset for target-dependent sentiment classification in English news articles.\n", "citation": "@InProceedings{Hamborg2021b,\n author = {Hamborg, Felix and Donnay, Karsten},\n title = {NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles},\n booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)},\n year = {2021},\n month = {Apr.},\n location = {Virtual Event},\n}\n", "homepage": "https://github.com/fhamborg/NewsMTSC/", "license": "MIT", "features": {"primary_gid": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_normalized": {"dtype": "string", "id": null, "_type": "Value"}, "targets": {"feature": {"Input.gid": {"dtype": "string", "id": null, "_type": "Value"}, "from": {"dtype": "uint32", "id": null, "_type": "Value"}, "to": {"dtype": "uint32", "id": null, "_type": "Value"}, "mention": {"dtype": "string", "id": null, "_type": "Value"}, "polarity": {"dtype": "float32", "id": null, "_type": "Value"}, "further_mentions": {"feature": {"from": {"dtype": "uint32", "id": null, "_type": "Value"}, "to": {"dtype": "uint32", "id": null, "_type": "Value"}, "mention": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "
|
|
|
1 |
+
{"rw": {"description": "NewsMTSC: A large, manually annotated dataset for target-dependent sentiment classification in English news articles.\n", "citation": "@InProceedings{Hamborg2021b,\n author = {Hamborg, Felix and Donnay, Karsten},\n title = {NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles},\n booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)},\n year = {2021},\n month = {Apr.},\n location = {Virtual Event},\n}\n", "homepage": "https://github.com/fhamborg/NewsMTSC/", "license": "MIT", "features": {"primary_gid": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_normalized": {"dtype": "string", "id": null, "_type": "Value"}, "targets": {"feature": {"Input.gid": {"dtype": "string", "id": null, "_type": "Value"}, "from": {"dtype": "uint32", "id": null, "_type": "Value"}, "to": {"dtype": "uint32", "id": null, "_type": "Value"}, "mention": {"dtype": "string", "id": null, "_type": "Value"}, "polarity": {"dtype": "float32", "id": null, "_type": "Value"}, "further_mentions": {"feature": {"from": {"dtype": "uint32", "id": null, "_type": "Value"}, "to": {"dtype": "uint32", "id": null, "_type": "Value"}, "mention": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "news_sentiment_newsmtsc", "config_name": "rw", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2579834, "num_examples": 7758, "dataset_name": "news_sentiment_newsmtsc"}, "test": {"name": "test", "num_bytes": 243931, "num_examples": 747, "dataset_name": "news_sentiment_newsmtsc"}, "validation": {"name": "validation", "num_bytes": 107098, "num_examples": 320, "dataset_name": "news_sentiment_newsmtsc"}}, "download_checksums": {"https://raw.githubusercontent.com/fhamborg/NewsMTSC/a96f785fd3110c202e05e63579ddb30043eef128/NewsSentiment/experiments/default/datasets/newsmtsc-rw/train.jsonl": {"num_bytes": 3292398, "checksum": "fb80ff05993dd59016c36abefaa7bd00d77cb0cb38a781c1f9edd9ad7c61471e"}, "https://raw.githubusercontent.com/fhamborg/NewsMTSC/a96f785fd3110c202e05e63579ddb30043eef128/NewsSentiment/experiments/default/datasets/newsmtsc-rw/dev.jsonl": {"num_bytes": 136349, "checksum": "d62a327eefa17f63c66ed221f31d0b4e140b46c58bdd9680df562523c860bf4b"}, "https://raw.githubusercontent.com/fhamborg/NewsMTSC/a96f785fd3110c202e05e63579ddb30043eef128/NewsSentiment/experiments/default/datasets/newsmtsc-rw/test.jsonl": {"num_bytes": 309929, "checksum": "64a6e2619734091a003eb555fd37b786f018032256e83c39ceac4649032e57ba"}}, "download_size": 3738676, "post_processing_size": null, "dataset_size": 2930863, "size_in_bytes": 6669539}, "mt": {"description": "NewsMTSC: A large, manually annotated dataset for target-dependent sentiment classification in English news articles.\n", "citation": "@InProceedings{Hamborg2021b,\n author = {Hamborg, Felix and Donnay, Karsten},\n title = {NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles},\n booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)},\n year = {2021},\n month = {Apr.},\n location = {Virtual Event},\n}\n", "homepage": "https://github.com/fhamborg/NewsMTSC/", "license": "MIT", "features": {"primary_gid": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_normalized": {"dtype": "string", "id": null, "_type": "Value"}, "targets": {"feature": {"Input.gid": {"dtype": "string", "id": null, "_type": "Value"}, "from": {"dtype": "uint32", "id": null, "_type": "Value"}, "to": {"dtype": "uint32", "id": null, "_type": "Value"}, "mention": {"dtype": "string", "id": null, "_type": "Value"}, "polarity": {"dtype": "float32", "id": null, "_type": "Value"}, "further_mentions": {"feature": {"from": {"dtype": "uint32", "id": null, "_type": "Value"}, "to": {"dtype": "uint32", "id": null, "_type": "Value"}, "mention": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "news_sentiment_newsmtsc", "config_name": "mt", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2579834, "num_examples": 7758, "dataset_name": "news_sentiment_newsmtsc"}, "test": {"name": "test", "num_bytes": 217938, "num_examples": 505, "dataset_name": "news_sentiment_newsmtsc"}, "validation": {"name": "validation", "num_bytes": 94303, "num_examples": 216, "dataset_name": "news_sentiment_newsmtsc"}}, "download_checksums": {"https://raw.githubusercontent.com/fhamborg/NewsMTSC/a96f785fd3110c202e05e63579ddb30043eef128/NewsSentiment/experiments/default/datasets/newsmtsc-mt/train.jsonl": {"num_bytes": 3292398, "checksum": "fb80ff05993dd59016c36abefaa7bd00d77cb0cb38a781c1f9edd9ad7c61471e"}, "https://raw.githubusercontent.com/fhamborg/NewsMTSC/a96f785fd3110c202e05e63579ddb30043eef128/NewsSentiment/experiments/default/datasets/newsmtsc-mt/dev.jsonl": {"num_bytes": 124042, "checksum": "728602b11d63deb64874e1933bb6b832596a25fd711235cc38d022d839b03738"}, "https://raw.githubusercontent.com/fhamborg/NewsMTSC/a96f785fd3110c202e05e63579ddb30043eef128/NewsSentiment/experiments/default/datasets/newsmtsc-mt/test.jsonl": {"num_bytes": 287381, "checksum": "765cb5979353dff55174b5f2bfd7026d55e86c02ed87189637ec73215eb1563d"}}, "download_size": 3703821, "post_processing_size": null, "dataset_size": 2892075, "size_in_bytes": 6595896}}
|
news_mtsc_dataset.py → news_sentiment_newsmtsc.py
RENAMED
@@ -59,7 +59,7 @@ class AllowNoFurtherMentionsFeatures(datasets.Features):
|
|
59 |
return super().encode_example(example)
|
60 |
|
61 |
|
62 |
-
class
|
63 |
"""NewsMTSC Dataset: A large, manually annotated dataset for target-dependent sentiment classification in political
|
64 |
news articles."""
|
65 |
|
|
|
59 |
return super().encode_example(example)
|
60 |
|
61 |
|
62 |
+
class NewsSentimentNewsmtsc(datasets.GeneratorBasedBuilder):
|
63 |
"""NewsMTSC Dataset: A large, manually annotated dataset for target-dependent sentiment classification in political
|
64 |
news articles."""
|
65 |
|