Should B.Pharm, C.Psych and M.Kes be listed credentials, now that Ahmed Ali M.Hassan loses its surname to the same guess? #998

An initial typed without a space before the surname (M.Hassan) has the same shape as a credential written in two chunks (B.Pharm, C.Psych). At the end of a name, S3 (credentials written in joined chunks) reads an unlisted word of that shape by position, the way S4 reads a bare ambiguous acronym. So when the name has words to spare, the surname becomes a suffix:

"Ahmed Ali M.Hassan"        →  given="Ahmed", family="Ali", suffix="M.Hassan"        (SUFFIX_OR_NAME)
"Ahmed Ali M.Hassan, PhD"   →  family="Ali", suffix="M.Hassan, PhD"                (SUFFIX_OR_NAME)
"Hassan, Ahmed M.Ali"       →  family="Hassan", suffix="M.Ali"                       (SUFFIX_OR_NAME)
"Ahmed M.Hassan"            →  family="M.Hassan"                                     (no words to spare)
"M.Hassan, Ahmed Ali"       →  family="M.Hassan"
"Ahmed Ali B.Pharm"         →  suffix="B.Pharm"                                      (SUFFIX_OR_NAME)
"Ahmed Ali M.Med"           →  suffix="M.Med"                                        (listed)

The parser already reports that it guessed (SUFFIX_OR_NAME). The credentials that share the shape are a short list of spellings, though, and listing them would take most of the guessing out of this shape.

Found by comparing against the Rust crate human_name, which splits after a dotted single letter (F.Joachim Weyl → given Joachim) and reads its test row X.Gironés as family Gironés.

How often, and which way the guess is right (measured 2026-11-02, tree 854087b)

Recipe: a token matching (?<![\w.])[A-ZÀ-Þ]\.[A-ZÀ-Þ][a-zà-ÿ'\-]{2,}(?![\w.]), across the local corpora orcid-researchers, ctgov-officials, patentsview-inventors, psc-individuals, nepal-candidates and cz-candidates, parsed with parse(). "Listed" means the token carries vocab:suffix. Whether the second chunk is a credential or a name was sorted by hand from a list of credential chunks (phil, med, pharm, psych, kes, kep, eng, physio, tech, sci, …).

Where the shape is read by position as a suffix, it is a credential about 2 times in 3, so flipping the default would lose more than it wins. Most of the 115 credentials are a short list of spellings. The top 15 unlisted spellings cover most of them, and several (the Indonesian M.Kes, M.Kep, M.Kom, S.Kom, S.Ked) are degrees the vocabulary does not hold at all.

Proposal: list the credentials, don't recognize them by shape

When: a two-chunk credential such as B.Pharm, C.Psych, M.Kes, M.Pharm, M.Sci, M.Kep, P.Eng, B.Physio, B.Med or M.Tech ends a name.

Then: it reads as a suffix because the vocabulary lists it (a measured batch through tools/vocab/, with bearer checks on each spelling), with no SUFFIX_OR_NAME report. S3's position reading of unlisted words stays as it is.

Because: a credential written in chunks belongs to a closed set that can be listed, while the shape is also written by other things. Besides a glued initial and surname, it is the writing of unspaced initials (#490's E.T. Smith, #995's Иванов И.И.). A shape rule narrow enough to separate those would still match P.Eng and C.Psych exactly.

Accepted: a glued initial and surname at the end of a name with words to spare (Ahmed Ali M.Hassan) keeps losing its surname to the suffix, reported as SUFFIX_OR_NAME. That was about 63 names in the corpora above.

Declined: reading the narrower shape (a single capital, then a capitalized chunk of three or more letters) as a name word by position. It cannot tell M.Hassan from P.Eng, and any unlisted credential would then read as the family.

Missing spaces this could correct

The 1,116 name readings are mostly the opening word (A.Michael Lincoff → given A.Michael) or the only word after the given name (Ahmed M.Hassan → family M.Hassan). The parts land in the right place, but an initial is stuck to a name. Some datasets routinely leave out the space after an initial (#995's Slavic data writes И.И.). So this belongs on the list of missing spaces the parser could restore, beside #490 (E.T. Smith) and #995. It is noted here and not proposed: inserting the space is a tokenization question, and it should be answered for all three shapes at once.

Open questions

• With the batch listed, how many of the 63 names does the position reading still take, and how many unlisted credentials remain?
• Comma shapes: the given part after a family comma (Hassan, Ahmed M.Ali, read by S5) gets the same answer from the vocabulary. Check the batch's grid for it.

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