ICE-ID: A Novel Historical Census Dataset for Longitudinal Identity Resolution
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866908849163730944 |
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| author | de Carvalho, Gonçalo Hora Popov, Lazar S. Kaatee, Sander Correia, Mário S. Thórisson, Kristinn R. Li, Tangrui Björnsson, Pétur Húni Sigurðarson, Eiríkur Smári Dibangoye, Jilles S. |
| author_facet | de Carvalho, Gonçalo Hora Popov, Lazar S. Kaatee, Sander Correia, Mário S. Thórisson, Kristinn R. Li, Tangrui Björnsson, Pétur Húni Sigurðarson, Eiríkur Smári Dibangoye, Jilles S. |
| contents | We introduce \textbf{ICE-ID}, a benchmark dataset comprising 984,028 records from 16 Icelandic census waves spanning 220 years (1703--1920), with 226,864 expert-curated person identifiers. ICE-ID combines hierarchical geography (farm$\to$parish$\to$district$\to$county), patronymic naming conventions, sparse kinship links (partner, father, mother), and multi-decadal temporal drift -- challenges not captured by standard product-matching or citation datasets. This paper presents an artifact-backed analysis of temporal coverage, missingness, identifier ambiguity, candidate-generation efficiency, and cluster distributions, and situates ICE-ID against classical ER benchmarks (Abt--Buy, Amazon--Google, DBLP--ACM, DBLP--Scholar, Walmart--Amazon, iTunes--Amazon, Beer, Fodors--Zagats). We also define a deployment-faithful temporal OOD protocol and release the dataset, splits, regeneration scripts, analysis artifacts, and a dashboard for interactive exploration. Baseline model comparisons and end-to-end ER results are reported in the companion methods paper. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_13792 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ICE-ID: A Novel Historical Census Dataset for Longitudinal Identity Resolution de Carvalho, Gonçalo Hora Popov, Lazar S. Kaatee, Sander Correia, Mário S. Thórisson, Kristinn R. Li, Tangrui Björnsson, Pétur Húni Sigurðarson, Eiríkur Smári Dibangoye, Jilles S. Artificial Intelligence Computation and Language Machine Learning Applications We introduce \textbf{ICE-ID}, a benchmark dataset comprising 984,028 records from 16 Icelandic census waves spanning 220 years (1703--1920), with 226,864 expert-curated person identifiers. ICE-ID combines hierarchical geography (farm$\to$parish$\to$district$\to$county), patronymic naming conventions, sparse kinship links (partner, father, mother), and multi-decadal temporal drift -- challenges not captured by standard product-matching or citation datasets. This paper presents an artifact-backed analysis of temporal coverage, missingness, identifier ambiguity, candidate-generation efficiency, and cluster distributions, and situates ICE-ID against classical ER benchmarks (Abt--Buy, Amazon--Google, DBLP--ACM, DBLP--Scholar, Walmart--Amazon, iTunes--Amazon, Beer, Fodors--Zagats). We also define a deployment-faithful temporal OOD protocol and release the dataset, splits, regeneration scripts, analysis artifacts, and a dashboard for interactive exploration. Baseline model comparisons and end-to-end ER results are reported in the companion methods paper. |
| title | ICE-ID: A Novel Historical Census Dataset for Longitudinal Identity Resolution |
| topic | Artificial Intelligence Computation and Language Machine Learning Applications |
| url | https://arxiv.org/abs/2506.13792 |