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22. Bengali Visual Genome 1.0
- Creator:
- Sen, Arghyadeep, Parida, Shantipriya, Kotwal, Ketan, Panda, Subhadarshi, Bojar, Ondřej, and Dash, Satya Ranjan
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- image and corpus
- Subject:
- multi-modal, neural machine translation, image captioning, Bengali captioning, and English-Bengali Multimodal Corpus
- Language:
- English and Bengali
- Description:
- Data ------- Bengali Visual Genome (BVG for short) 1.0 has similar goals as Hindi Visual Genome (HVG) 1.1: to support the Bengali language. Bengali Visual Genome 1.0 is the multi-modal dataset in Bengali for machine translation and image captioning. Bengali Visual Genome is a multimodal dataset consisting of text and images suitable for English-to-Bengali multimodal machine translation tasks and multimodal research. We follow the same selection of short English segments (captions) and the associated images from Visual Genome as HGV 1.1 has. For BVG, we manually translated these captions from English to Bengali taking the associated images into account. The manual translation is performed by the native Bengali speakers without referring to any machine translation system. The training set contains 29K segments. Further 1K and 1.6K segments are provided in development and test sets, respectively, which follow the same (random) sampling from the original Hindi Visual Genome. A third test set is called the ``challenge test set'' and consists of 1.4K segments. The challenge test set was created for the WAT2019 multi-modal task by searching for (particularly) ambiguous English words based on the embedding similarity and manually selecting those where the image helps to resolve the ambiguity. The surrounding words in the sentence however also often include sufficient cues to identify the correct meaning of the ambiguous word. Dataset Formats --------------- The multimodal dataset contains both text and images. The text parts of the dataset (train and test sets) are in simple tab-delimited plain text files. All the text files have seven columns as follows: Column1 - image_id Column2 - X Column3 - Y Column4 - Width Column5 - Height Column6 - English Text Column7 - Bengali Text The image part contains the full images with the corresponding image_id as the file name. The X, Y, Width and Height columns indicate the rectangular region in the image described by the caption. Data Statistics --------------- The statistics of the current release are given below. Parallel Corpus Statistics -------------------------- Dataset Segments English Words Bengali Words ---------- -------- ------------- ------------- Train 28930 143115 113978 Dev 998 4922 3936 Test 1595 7853 6408 Challenge Test 1400 8186 6657 ---------- -------- ------------- ------------- Total 32923 164076 130979 The word counts are approximate, prior to tokenization. Citation -------- If you use this corpus, please cite the following paper: @inproceedings{hindi-visual-genome:2022, title= "{Bengali Visual Genome: A Multimodal Dataset for Machine Translation and Image Captioning}", author={Sen, Arghyadeep and Parida, Shantipriya and Kotwal, Ketan and Panda, Subhadarshi and Bojar, Ond{\v{r}}ej and Dash, Satya Ranjan}, editor={Satapathy, Suresh Chandra and Peer, Peter and Tang, Jinshan and Bhateja, Vikrant and Ghosh, Anumoy}, booktitle= {Intelligent Data Engineering and Analytics}, publisher= {Springer Nature Singapore}, address= {Singapore}, pages = {63--70}, isbn = {978-981-16-6624-7}, doi = {10.1007/978-981-16-6624-7_7}, }
- Rights:
- Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB
23. Bibliografie cizojazyčných bohemikálních tisků do roku 1800 /
- Creator:
- Jelínková, Andrea,
- Type:
- text, statický obraz, and brožury
- Subject:
- Bibliografie. Katalogy, bibliografie, databáze, tisky staré, bohemika, knihověda, bibliografie oborové a tematické, rejstříky časopisů, and staré tisky
- Language:
- Czech
- Description:
- Název z obálky and Pod názvem: Akademie věd České republiky, Knihovna Akademie věd ČR
- Rights:
- unknown
24. Břeclav - Pohansko.
- Creator:
- Macháček, Jiří,
- Type:
- text, statický obraz, and monografie kolektivní
- Subject:
- Archeologie, archeologie, výzkumy, archeologie, nálezy, hradiště, pohřebiště, české (československé) sborníky a kolektivní monografie, Velká Morava, Čechy v době velkomoravské (833–906/907), dějiny společnosti, and archeologické výzkumy, archeologie v muzeích a archivech
- Language:
- Czech
- Rights:
- unknown
25. ČAS :
- Type:
- text and časopisy
- Subject:
- Seriálové publikace. Periodika, Masaryk, Tomáš Garrigue,, masarykiana, and česká periodika
- Language:
- Czech
- Rights:
- unknown
26. Časopis zdravotnického práva a bioetiky
- Type:
- model:periodicalitem and TEXT
- Language:
- Czech, Slovak, and English
- Description:
- 2
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public
27. Časopis zdravotnického práva a bioetiky
- Type:
- model:periodicalitem and TEXT
- Language:
- Czech
- Description:
- 1
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public
28. Časopis zdravotnického práva a bioetiky
- Type:
- model:periodicalitem and TEXT
- Language:
- Czech, Slovak, and English
- Description:
- 1
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
29. Časopis zdravotnického práva a bioetiky
- Type:
- model:periodicalitem and TEXT
- Language:
- Czech, Slovak, and English
- Description:
- 2
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public
30. CERED baseline models
- Creator:
- Šimečková, Zuzana and Straka, Milan
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- mlmodel, text, and languageDescription
- Subject:
- relationship extraction
- Language:
- Czech
- Description:
- Relationship extraction models for the Czech language. Models are trained on CERED (dataset created by distant supervision on Czech Wikipedia and Wikidata) and recognize a subset of Wikidata relations (listed in CEREDx.LABELS). We supply a demo.py that performs inference on user-defined input and requirements.txt file for pip. Adapt the demo code to use the model. Both the dataset and the models are presented in Relationship Extraction thesis.
- Rights:
- Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), PUB, and http://creativecommons.org/licenses/by-nc-sa/4.0/