README.md

metadata

task_categories:
  - feature-extraction
tags:
  - table-embeddings
  - column-type-annotation
  - column-property-annotation
  - tabular

TabEmb Representations

Precomputed LLM column embeddings used by the TabEmb pipeline for column type annotation (CTA) and column property annotation (CPA).

TODO before publishing: fill in the sections below, and confirm the licensing terms of each source benchmark permit redistributing derived embeddings (SOTAB, T2D, WebTables, WikiTables each have their own license/citation requirements).

Contents

Each subdirectory follows <data_dir_name>/<task>/ (task is cta or cpa), containing pickle files named:

<task>_<data_name>_<split>_<row_examples>_<model>_<quantized>_<mean_pooling>_<layer_offset>_<layer_pooling>.pkl

Datasets included:

• dataset-sota-dbpedia
• dataset-t2d
• sotabv2
• webtables
• wikitable

Pickle schema

Each .pkl file is a dict with:

• table_id: array of table identifiers
• column_id: array of column indices
• embedding: array of embedding vectors (one per column)
• label: array of integer class labels

Loading

import pickle
with open("dataset-t2d/cta/cta_dataset-t2d_train_25_mistral_True_True_1_none.pkl", "rb") as f:
    data = pickle.load(f)

License / Citation

TODO: state the license for this derived data and cite the original benchmarks (SOTAB, T2D, WDC WebTables, WikiTables).