metadata
dataset_info:
features:
- name: ID
dtype: int32
- name: Task Name
dtype: string
- name: PDF
dtype:
pdf:
decode: false
- name: Language
dtype: string
- name: Task
dtype: string
- name: Content
dtype: string
- name: TXT Filename
dtype: string
- name: PDF Filename
dtype: string
splits:
- name: parallel
num_bytes: 6844760
num_examples: 96
- name: not_parallel
num_bytes: 2359134
num_examples: 47
download_size: 8100216
dataset_size: 9203894
configs:
- config_name: default
data_files:
- split: parallel
path: data/parallel-*
- split: not_parallel
path: data/not_parallel-*
Dataset Card: PISA Multimodal (Parallel & Not-Parallel)
Summary
This dataset contains 48 parallel multimodal samples (paired TXT↔PDF) derived from PISA studies up to 2012, plus 47 non-parallel samples (TXT-only or PDF-only). Each sample may include multiple questions. Content is available in German and English.
Source & usage: Materials are published by the OECD and are provided here for non-commercial use only. Please verify that your usage complies with OECD terms.
Quality note: Some of the parallel samples are noisy (e.g., OCR artifacts or imperfect alignments). These are explicitly labeled in the filename so they can be filtered out during experiments.
Organization & Splits
train
— parallel split: 48 samples (TXT and matching PDF).not_parallel
— 47 samples where only TXT or only PDF is present.
Note: In this split, one ofContent
orPDF
can benull
. (Counts reflect the provided corpus; they may change if you add/remove files.)
Languages
- German:
deu_Latn
- English:
eng_Latn
Tasks
- Reading comprehension
- Math problem solving
Data Fields (Columns)
ID
(int32) — Running index of the sample (per build script).Task Name
(string) — Base name of the material (filename stem before the last underscore), e.g.,Bookshelves
.PDF
(Pdf feature) — Full PDF object (stored viadatasets.Pdf
). May benull
innot_parallel
if missing.Language
(string) — Language code of the folder, e.g.,deu_Latn
oreng_Latn
.Task
(string) — Task category from the folder name:reading
ormath
.Content
(string) — Full text from the paired.txt
. May benull
innot_parallel
if missing.TXT Filename
(string) — Basename of the associated.txt
file (if present).PDF Filename
(string) — Basename of the associated.pdf
file (if present).
Source Data & Provenance
- Origin: Items compiled from OECD PISA materials (≤2012).
- Derivation: Parallel pairs were formed by matching TXT and PDF stems; the
not_parallel
split contains items missing one counterpart.
Licensing & Usage
- License: Other / Non-commercial. The content is published by the OECD. Redistribution and use should comply with OECD non-commercial terms. This card is not legal advice—please review the official terms for your use case.
How to Load
from datasets import load_dataset
# From the Hub (replace with your repo id)
ds = load_dataset("your-username/your-dataset")
# Parallel split
train = ds["train"]
# Not-parallel split
not_parallel = ds["not_parallel"]
# Example access
row = train[0]
print(row["Task Name"], row["Language"], row["Task"])
# PDF is a Pdf feature record with a path/bytes:
print(row["PDF"])
Intended Uses & Limitations
- Intended: research on multimodal QA, OCR+NLP, cross-lingual evaluation, dataset tooling.
- Not intended: commercial exploitation of OECD content; deployment without verifying rights.
- Limitations: Some samples include multiple questions per PDF/TXT;
not_parallel
items are incomplete by design; some parallel items are flagged as noisy in filenames.
Citation
If you use this dataset, please cite the OECD PISA materials appropriately and reference this dataset card.