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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).
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-dbpediadataset-t2dsotabv2webtableswikitable
Pickle schema
Each .pkl file is a dict with:
table_id: array of table identifierscolumn_id: array of column indicesembedding: 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).
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