All datasets released under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.
- ocp_entities_v0.csv
- ocp_media_types_v0.csv
- ocp_sentences_v0.csv
- utterance_tags_v0.2.csv
- corefiob_v0.1.txt
- world_names_v0.2.csv
media playback related entities scraped from wikidata via SPARQL queries, more info in OCP-dataset repo
['film_genre', 'cartoon_genre', 'news_streaming_service',
'media_type_documentary', 'media_type_adult', 'media_type_bw_movie', 'podcast_genre',
'comic_streaming_service', 'music_genre', 'media_type_video_episodes', 'anime_genre',
'media_type_audio', 'media_type_bts', 'media_type_silent_movie',
'audiobook_streaming_service', 'radio_drama_genre', 'media_type_podcast',
'radio_theatre_company', 'media_type_short_film', 'media_type_movie', 'news_provider',
'documentary_genre', 'radio_theatre_streaming_service', 'podcast_streaming_service',
'media_type_tv', 'comic_name', 'media_type_adult_audio', 'media_type_news',
'media_type_music', 'media_type_cartoon', 'documentary_streaming_service',
'cartoon_streaming_service', 'anime_streaming_service', 'media_type_hentai',
'movie_streaming_service', 'media_type_trailer', 'shorts_streaming_service', 'video_genre',
'porn_streaming_service', 'playback_device', 'media_type_game', 'playlist_name',
'media_type_video', 'media_type_visual_story', 'media_type_radio_theatre',
'media_type_audiobook', 'porn_genre', 'book_genre', 'media_type_anime', 'sound',
'media_type_radio', 'album_name', 'country_name', 'generic_streaming_service',
'tv_streaming_service', 'radio_drama_name', 'film_studio', 'video_streaming_service',
'short_film_name', 'tv_channel', 'youtube_channel', 'bw_movie_name', 'audiobook_narrator',
'radio_drama', 'radio_program_name', 'game_name', 'series_name', 'artist_name', 'tv_genre',
'hentai_name', 'podcast_name', 'music_streaming_service', 'silent_movie_name', 'book_name',
'gaming_console_name', 'book_author', 'record_label', 'radio_streaming_service',
'game_genre', 'anime_name', 'documentary_name', 'cartoon_name', 'audio_genre', 'song_name',
'movie_name', 'porn_film_name', 'comics_genre', 'radio_program', 'porn_site',
'pornstar_name']semi-synthetic dataset to classify OCP media types, generated via sentence templates created with LLMs + entities from dataset above
more info in OCP-dataset repo
AUDIO = 1 # things like ambient noises
MUSIC = 2
VIDEO = 3 # eg, youtube videos
AUDIOBOOK = 4
GAME = 5 # because it shares the verb "play", mostly for disambguation
PODCAST = 6
RADIO = 7 # live radio
NEWS = 8 # news reports
TV = 9 # live tv stream
MOVIE = 10
TRAILER = 11
AUDIO_DESCRIPTION = 12 # narrated movie for the blind
VISUAL_STORY = 13 # things like animated comic books
BEHIND_THE_SCENES = 14
DOCUMENTARY = 15
RADIO_THEATRE = 16
SHORT_FILM = 17 # typically movies under 45 min
SILENT_MOVIE = 18
VIDEO_EPISODES = 19 # tv series etc
BLACK_WHITE_MOVIE = 20
CARTOON = 21
ANIME = 22
ADULT = 69 # for content filtering
HENTAI = 70 # for content filtering
ADULT_AUDIO = 71 # for content filtering
music, What's the latest on christian hip hop
radio_drama, find me a fascinating radio theatre program on RSS feed
silent_movie, Can you find silent films from Andorra on Youtube Movies
ad, Describe Ya z toboyu with audio for the visually impaired on Moviechi
cartoon, watch a cartoon on TV
documentary, documentary on ancient mysteries
hentai, Start anime for mature audiences - let's see what's out there
sentences tagged as media playback related or not, samples tagged as OCP come from ocp_media_types_v0.csv the others from datasets in this repository
more info in OCP-dataset repo
dataset v0.1 contained 1187 labeled utterances that fall into three categories: COMMAND, QUESTION, and SENTENCE. Each label has sub-labels that describe the type of utterance, such as ACTION, DENIAL, QUERY, and REQUEST.
v0.2 extended number of samples to ~5500 via ChatGPT
The purpose of this dataset is to provide labeled examples of various types of commands, questions, and sentences that can be used for training natural language processing (NLP) models.
- COMMAND: This label refers to statements that give instructions or orders. These can be further divided into sub-labels ACTION and DENIAL.
- ACTION: This sub-label refers to commands that instruct the listener to perform an action.
- DENIAL: This sub-label refers to commands that instruct the listener to refrain from performing an action.
- QUESTION: This label refers to statements that ask for information. These can be further divided into sub-labels QUERY, YESNO and REQUEST.
- QUERY: This sub-label refers to questions that ask for information or definitions.
- REQUEST: This sub-label refers to questions that make a request.
- YESNO: This sub-label refers to questions that can be answered with a simple "yes" or "no"
- SENTENCE: This label refers to statements that do not fit into either of the above categories.
- EXCLAMATION: This sub-label refers to sentences that express strong emotions such as excitement, surprise, or admiration.
- SOCIAL: This sub-label refers to sentences that are used in social situations to express well-wishes or greetings.
- STATEMENT: This sub-label refers to sentences that make a statement or convey information.
COMMAND:ACTION,Boil some water
COMMAND:ACTION,Bring me a glass of water
COMMAND:ACTION,Brush your teeth
COMMAND:ACTION,Call John
COMMAND:DENIAL,Don't eat that, it's spoiled
COMMAND:DENIAL,It is prohibited to smoke in this building
COMMAND:DENIAL,Smoking is strictly prohibited in this area
COMMAND:DENIAL,Stay away from the edge
COMMAND:DENIAL,Stop running right now
COMMAND:DENIAL,You are not allowed to go outside
COMMAND:DENIAL,You are not allowed to smoke in this area
QUESTION:QUERY,How many people are in the room
QUESTION:QUERY,How much does it cost
QUESTION:QUERY,What are the office hours
QUESTION:QUERY,What can we speak
QUESTION:QUERY,What day is Christmas
QUESTION:REQUEST,Would you mind passing me a napkin
QUESTION:REQUEST,Would you mind passing me a tissue
QUESTION:REQUEST,Would you mind passing me the salt
QUESTION:REQUEST,Would you mind passing me the salt, please
QUESTION:YESNO,Are Spanish and German different languages
QUESTION:YESNO,Are airplanes flown inside
QUESTION:YESNO,Are all dogs friendly
QUESTION:YESNO,Are ants strong
SENTENCE:EXCLAMATION,What an amazing experience
SENTENCE:EXCLAMATION,What an impressive accomplishment
SENTENCE:EXCLAMATION,What an impressive performance by the dancers
SENTENCE:SOCIAL,Congratulations on your promotion
SENTENCE:SOCIAL,Enjoy your weekend
SENTENCE:SOCIAL,Get well soon
SENTENCE:SOCIAL,Good luck on your exam
SENTENCE:SOCIAL,Good luck with your interview
SENTENCE:SOCIAL,Good morning
SENTENCE:STATEMENT,The sky is so blue today
SENTENCE:STATEMENT,The sun is a star that is located at the center of our solar system
SENTENCE:STATEMENT,The sun rises in the east and sets in the west
This is a dataset for coreference resolution consisting of 184 sentences in CoNNL format. The dataset has been manually annotated to include coreference mentions of masculine, feminine, and inanimate entities. Additional entries have been included to expand the variety of coreference cases present in the dataset.
Each line of the dataset represents a token and its corresponding part-of-speech tag and entity tag. The entity tags denote the start and end of an entity mention, and whether it is a masculine, feminine, or inanimate entity, and if it is the coreference mention, using the BIO scheme.
The dataset is suitable for training feature extractors for coreference resolution models.
The annotations follow the following scheme:
- B-ENTITY-MALE: Beginning of a male entity mention
- I-ENTITY-MALE: Inside of a male entity mention
- B-ENTITY-FEMALE: Beginning of a female entity mention
- I-ENTITY-FEMALE: Inside of a female entity mention
- B-ENTITY-INANIMATE: Beginning of a non-human entity mention
- I-ENTITY-INANIMATE: Inside of a non-human entity mention
- B-ENTITY-PLURAL: Beginning of a plural entity mention
- I-ENTITY-PLURAL: Inside of a plural entity mention
- B-COREF-MALE: Beginning of a coreference mention of a male entity
- I-COREF-MALE: Inside of a coreference mention of a male entity
- B-COREF-FEMALE: Beginning of a coreference mention of a female entity
- I-COREF-FEMALE: Inside of a coreference mention of a female entity
- B-COREF-INANIMATE: Beginning of a coreference mention of a non-human entity
- I-COREF-INANIMATE: Inside of a coreference mention of a non-human entity
- B-COREF-PLURAL: Beginning of a coreference mention of a plural entity
- I-COREF-PLURAL: Inside of a coreference mention of a plural entity
Korgoth PROPN B-ENTITY-MALE
of ADP I-ENTITY-MALE
Barbaria PROPN I-ENTITY-MALE
is AUX O
here ADV O
, PUNCT O
He PRON B-COREF-MALE
is AUX O
a DET O
savage NOUN O
! PUNCT O
Here ADV O
is AUX O
the DET B-ENTITY-INANIMATE
book NOUN I-ENTITY-INANIMATE
now ADV O
take VERB O
it PRON B-COREF-INANIMATE
This dataset contains a list of 1664 names with their respective gender and language. The dataset was created for educational and research purposes and can be used for various tasks such as gender classification, language detection, and name analysis.
The data is provided in a CSV (comma-separated values) format, with the following columns:
- label: The gender of the name, can be either male or female
- name: The name itself
- lang: The language of the name in full BCP47 format, such as en-US for American English or zh-CN for Simplified Chinese.
male,Eugen,ro-RO
female,Ingrid,sv-FI
male,Igor,hr-BA
female,Cecilia,es-ES
female,Susanne,de-DE
male,Yuriy,uk-UA
male,Carlos,es-ES
male,Lluís,ca-ES
male,Franklin,en-US
female,Kumiko,ja-JP
female,Yun-Xia,zh-CN
male,Muhammad,ar-EG
male,Ionut,ro-RO
male,Vicente,pt-BR
female,Gizem,tr-TR
male,Dominic,en-GB
male,Siu-Ming,zh-HK
male,Olivier,fr-FR
female,Martina,es-AR