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---
dataset_info:
features:
- name: wikicaps_id
dtype: int64
- name: wikimedia_file
dtype: string
- name: caption
dtype: string
- name: tokens
sequence: string
- name: num_tok
dtype: int64
- name: sentence_spans
sequence: string
- name: sentence_languages
sequence: string
- name: num_sent
dtype: int64
- name: min_sent_len
dtype: int64
- name: max_sent_len
dtype: int64
- name: num_ne
dtype: int64
- name: ne_types
sequence: string
- name: ne_texts
sequence: string
- name: num_nouns
dtype: int64
- name: num_propn
dtype: int64
- name: num_conj
dtype: int64
- name: num_verb
dtype: int64
- name: num_sym
dtype: int64
- name: num_num
dtype: int64
- name: num_adp
dtype: int64
- name: num_adj
dtype: int64
- name: ratio_ne_tok
dtype: float64
- name: ratio_noun_tok
dtype: float64
- name: ratio_propn_tok
dtype: float64
- name: ratio_all_noun_tok
dtype: float64
- name: image_path
dtype: string
splits:
- name: train
num_bytes: 398344229
num_examples: 295886
- name: test
num_bytes: 6727191
num_examples: 5000
download_size: 183918204
dataset_size: 405071420
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
license: cc-by-sa-4.0
language:
- en
pretty_name: WISMIR 3
size_categories:
- 100K<n<1M
---
# WISMIR3: A Multi-Modal Dataset to Challenge Text-Image Retrieval Approaches
This repository holds the WISMIR3 dataset. For more information, please refer to the paper:
```bibtex
@inproceedings{
schneider2024wismir,
title={{WISMIR}3: A Multi-Modal Dataset to Challenge Text-Image Retrieval Approaches},
author={Florian Schneider and Chris Biemann},
booktitle={3rd Workshop on Advances in Language and Vision Research (ALVR)},
year={2024},
url={https://openreview.net/forum?id=Q93yqpfECQ}
}
```
## Columns
| ColumnId | Description | Datatype |
|-------------------|---------------------------------------------------------------------------|-----------|
| wikicaps_id | ID (line number) of the row in the original WikiCaps Dataset __img_en__ | int |
| wikimedia_file | Wikimedia File ID of the Image associated with the Caption | str |
| caption | Caption of the Image | str |
| image_path | Local path to the (downloaded) image | str |
| num_tok | Number of Tokens in the caption | int |
| num_sent | Number of Sentences in the caption | int |
| min_sent_len | Minimum number of Tokens in the Sentences of the caption | int |
| max_sent_len | Maximum number of Tokens in the Sentences of the caption | int |
| num_ne | Number of Named Entities in the caption | int |
| num_nouns | Number of Tokens with NOUN POS Tag | int |
| num_propn | Number of Tokens with PROPN POS Tag | int |
| num_conj | Number of Tokens with CONJ POS Tag | int |
| num_verb | Number of Tokens with VERB POS Tag | int |
| num_sym | Number of Tokens with SYM POS Tag | int |
| num_num | Number of Tokens with NUM POS Tag | int |
| num_adp | Number of Tokens with ADP POS Tag | int |
| num_adj | Number of Tokens with ADJ POS Tag | int |
| ratio_ne_tok | Ratio of tokens associated with Named Entities vs all Tokens | int |
| ratio_noun_tok | Ratio of tokens tagged as NOUN vs all Tokens | int |
| ratio_propn_tok | Ratio of tokens tagged as PROPN vs all Tokens | int |
| ratio_all_noun_tok| Ratio of tokens tagged as PROPN or NOUN vs all Tokens | int |
| fk_re_score | Flesch-Kincaid Reading Ease score of the Caption *** | int |
| fk_gl_score | Flesch-Kincaid Grade Level score of the Caption *** | int |
| dc_score | Dale-Chall score of the Caption *** | int |
| ne_texts | Surface form of detected NamedEntities | List[str] |
| ne_types | Types of the detected NamedEntities (PER, LOC, GPE, etc.) | List[str] |
***
See [https://en.wikipedia.org/wiki/List_of_readability_tests_and_formulas](https://en.wikipedia.org/wiki/List_of_readability_tests_and_formulas) for more information about
Readability Scores
## WikiCaps publication
WISMIR3 is based on the WikiCaps dataset. For more information about the WikiCaps, see [https://www.cl.uni-heidelberg.de/statnlpgroup/wikicaps/](https://www.cl.uni-heidelberg.de/statnlpgroup/wikicaps/)
```bibtex
@inproceedings{schamoni-etal-2018-dataset,
title = "A Dataset and Reranking Method for Multimodal {MT} of User-Generated Image Captions",
author = "Schamoni, Shigehiko and
Hitschler, Julian and
Riezler, Stefan",
editor = "Cherry, Colin and
Neubig, Graham",
booktitle = "Proceedings of the 13th Conference of the Association for Machine Translation in the {A}mericas (Volume 1: Research Track)",
month = mar,
year = "2018",
address = "Boston, MA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/W18-1814",
pages = "140--153",
}
```
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