whatsername

Figure out what someone's name actually is.

whatsername is a deterministic Python parser that splits a raw author-name string into structured components — title, first, middle, last, suffix, nickname — across Latin, Chinese, Japanese, Korean, Cyrillic, and Arabic / Persian scripts. It's the name parser extracted from the OpenAlex author entity resolution pipeline.

It is deterministic and fast (no network, no model weights), and every parse comes with a confidence score so you can route the hard cases to a human or an LLM.

from whatsername import parse_name

parse_name("John Maynard Smith")
# {'first': 'john', 'middle': 'maynard', 'last': 'smith', 'confidence': 'medium', ...}
# (3 tokens, no surname prefix -> the boundary is a guess, hence 'medium')

parse_name("Smith, John M.")             # comma form -> surname is explicit
# {'first': 'john', 'middle': 'm.', 'last': 'smith', 'confidence': 'high', ...}

parse_name("John M. Harris Jr MD")       # post-nominal credentials removed
# {'first': 'john', 'middle': 'm.', 'last': 'harris', 'suffix': 'jr', ...}

parse_name("张伟")                        # Chinese: surname-first
# {'first': 'wei', 'last': 'zhang', 'confidence': 'medium', ...}

Install

pip install whatsername

For better romanization of Japanese, Korean, and Cyrillic names, install the optional extra (the parser still works without it, at lower confidence):

pip install "whatsername[cjk]"

What you get back

parse_name(s) returns a dict. All string values are lowercase ASCII (diacritics removed, apostrophes dropped, hyphens and initials' periods preserved), or None.

key	example	notes
title	dr.	recognized academic/professional titles
first	john	given name
middle	maynard	middle name(s) / patronymic
last	smith	family name (compound prefixes like van der kept)
suffix	jr., phd	generational + post-nominal credentials
nickname	jack	text found in (...) / [...]
confidence	high	high | medium | low — threshold on this

Confidence is the whole point of routing:

• high — comma-delimited (Last, First), a clear compound surname prefix, or a simple 1–2 token Latin name.
• medium — 3+ token Latin with no prefix (surname boundary is a guess), or a CJK/Korean name resolved via the surname tables.
• low — Arabic/Persian (short vowels aren't written), ambiguous CJK, or Cyrillic transliteration. Good candidates to send to an LLM.

The OpenAlex-internal form

parse_human_name(s) returns the exact 6-field form OpenAlex uses for author matching: empty strings instead of None, surname particles stripped from last (so "de Oliveira" and "Oliveira" match), and a nameparser HumanName fallback for low-confidence Latin names.

Accuracy

Benchmarked against the public human-name-parser-gold-standard (15,309 OpenAlex author names):

metric	accuracy
Full match (all 6 fields exact)	88.8%
last (family name)	90.6%
last (surname particles stripped, i.e. matching-relevant)	91.4%
first	94.3%
middle	94.7%
title / suffix / nickname	≥99.5%

Run it yourself:

pip install pytest
pytest tests/test_benchmark.py -s

The largest error sources are inherent and hard: compound-surname boundaries, name-order disambiguation in romanized CJK names, and unusual scripts. That's what the confidence field is for.

About the benchmark. The gold standard is LLM-annotated — each name was parsed by Claude Opus 4.6, not labeled by hand. It's a strong reference set but not infallible, especially on the same hard cases the parser struggles with (compound surnames, CJK name order, rare scripts). Treat the accuracy numbers as indicative, not gospel.

Why is this GPL-licensed?

whatsername depends on Unidecode for transliteration (Chinese pinyin, Cyrillic, Arabic fallback), and Unidecode is licensed under the GPL. A project that depends on a GPL library must itself be GPL-compatible, so whatsername is released under the GPL-3.0-or-later. If you need a permissively-licensed name parser, you'll want a different library (or one that doesn't transliterate non-Latin scripts).

Credits

Built by OpenAlex / OurResearch as part of the author entity resolution (AER) work. The deterministic parser and its surname gazetteers come from the OpenAlex data pipeline; the benchmark was generated with Claude Opus 4.6. See the gold standard repo for the labeling protocol and reproduction harness.

License

GPL-3.0-or-later. See LICENSE.