wismir3 / README.md
floschne's picture
Update README.md
e07cc80 verified
|
raw
history blame
No virus
5.21 kB
metadata
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:

@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 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/

@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",
}