Datasetpublic

ehoseinz/tabemb-representations

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… See the full description on the dataset page: https://huggingface.co/datasets/ehoseinz/tabemb-representations.

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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).

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

python

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).