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Abstract We present the architecture and algorithms behind Matchsimile, an approximate string matching lookup tool especially designed for extracting person and company names from large texts. Part of a larger information extraction environment, this specific engine receives a large set of proper names to search for, a text to search, and search options; and outputs all the occurrences of the names found in the text. Beyond the similarity search capabilities applied at the intraword level, the tool considers a set of specific person name formation rules at the word level, such as combination, abbreviation, duplicity detections, ordering, word omission and insertion, among others. This engine is used in a successful commercial application (also named Matchsimile), which allows searching for lawyer names in official law publications.
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Stored only when both papers are in the corpus — 25 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.