entity-resolution
dutch-law-enforcement-entity-resolution-dataset
Dutch Law Enforcement Entity Resolution Benchmark
A collection of synthetic benchmark datasets for entity resolution and record linkage research, modelled on real Dutch and EU/EEA law enforcement data schemas.
All data is 100% synthetic.
No records correspond to real persons, vehicles, phone numbers, transactions, or criminal histories. Every name, date, plate number, IBAN, IMSI, and identifier is procedurally generated. The datasets are freely usable, shareable, and… See the full description on the dataset page: https://huggingface.co/datasets/zal-analytics-core/dutch-law-enforcement-entity-resolution-dataset.amc26-entity-resolution-embeddings-test
AMC26 — TEST-Split Business Entity Resolution Embeddings (multilingual-e5-base)
Precomputed sentence embeddings for the test split of the Amazon ML Challenge 2026
business entity-resolution task. Same pipeline, same model and same channels as the
train-split release,
so the two are directly comparable.
Purpose: blocking / candidate retrieval. For each Source 1 business, narrow the
~10M-record pool down to a shortlist worth scoring with a real pairwise model.
What is… See the full description on the dataset page: https://huggingface.co/datasets/rishavk77/amc26-entity-resolution-embeddings-test.business-entity-resolution-normalized
Business Entity Resolution: normalised records
Normalised copies of the six source files of the ML Challenge 2026 Business Entity Resolution task
(business records from three sources, US / India in train, plus France in test).
The goal of the task is to find, for every Source 1 record, the Source 2 / Source 3 records that describe the same business.
File
Rows
train_s1.parquet
2,206,821
train_s2.parquet
5,034,616
train_s3.parquet
5,285,603
test_s1.parquet
1,732… See the full description on the dataset page: https://huggingface.co/datasets/vc940/business-entity-resolution-normalized.mlc-2026-entity-resolution-checkpointsamazon-mlc-2026-business-entity-resolution
Amazon ML Challenge 2026 — Business Entity Resolution
Backup mirror of the official challenge resources for the Amazon ML Challenge 2026
"Business Entity Resolution" problem statement.
Contents
student_resource.zip — the official student resource package: training/test
TSVs (dataset/train/, dataset/test/), README.md (full problem statement),
Documentation_template.md, and utils/validate_submission.py.
problem-statement/ — the original problem statement images and… See the full description on the dataset page: https://huggingface.co/datasets/Ayush-Singh/amazon-mlc-2026-business-entity-resolution.amc26-entity-resolution-embeddings
AMC26 — Business Entity Resolution Embeddings (multilingual-e5-base)
Precomputed sentence embeddings for the Amazon ML Challenge 2026 business
entity-resolution task. Vectors cover the full training split and exist only to
power blocking / candidate retrieval: for each Source 1 business, find the handful of
Source 2 / Source 3 records that might be the same business.
Embedding the 12.5M records is the expensive, tedious part of this task. These files let
you skip it and go… See the full description on the dataset page: https://huggingface.co/datasets/rishavk77/amc26-entity-resolution-embeddings.