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Probabilistic tool for word segmentation to grammar-based units.

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About

Substitus is a computer program for linguistics-based word decomposition. The name is an abbreviation of the phrase substitutive segmenter which references to the used “method of squares” proposed by Joseph Harold Greenberg and independently reinvented and further developed while writing this work. Primarily, the application is designed to segment words (in arbitrary language), but it can handle any sequences. All it needs to work is a frequency dictionary of the processed language (100,000 word forms or more). You will find more details in the thesis (see the official archive).

Substitus is implemented in Java 8 as a console application. It is distributed in a single JAR file (less than 1 MB), with no library dependencies.

Example

$ echo "strawberry" | java -jar substitus.jar segmentize-words \
    --frequency-list english.fwl \
    --output-format html \
    --verbosity 1

Segmentation s trawberry:   0.00% ... no evidence
Segmentation s trawberry:   0.00% ... no evidence
Segmentation st rawberry:   0.00% ... no evidence
Segmentation str awberry:  15.65% ... [st-] × [-uck, -eaming, -eam]
Segmentation stra wberry:   2.29% ... [co-, cro-, ro-] × [-tton, -ps, -pped]
Segmentation straw berry:  58.05% ... [black-, blue-, gold-] × [-ford, -man, -son]
Segmentation strawb erry:   1.79% ... [thi-, m-, v-] × [-ale, -oss, -ridge]
Segmentation strawbe rry:   0.32% ... [so-, sha-, co-] × [-ar]
Segmentation strawber ry:   7.72% ... [count-, ma-, ga-] × [-y]
Segmentation strawberr y:  95.10% ... [universit-, part-, compan-] × [-ies, -ies., -ries]

s 0.00 t 0.00 r 0.16 a 0.02 w 0.58 b 0.02 e 0.00 r 0.08 r 0.95 y
straw berr y

The output consists of (optional) segmentation details and two results, probabilistic and binarised. The binarised version is just a simple modification of the probabilistic one.

Frequency word list

In order to learn grammar, Substitus needs a frequency word list. The file consist of pairs frequency – word. The columns may be divided by either spaces or tabs.

english.fwl

582770  the
268766  to
256531  and
…
1169    attention
1168    45
1166    focus
…
1       university-educated
1       W.K.
1       Zhuan

Comparison with human segmentation

Substitus settings:

  • frequency word list: two million words, web-corpus-based
  • split function: segmentability ≥ 0.5 || (segmentability > 0 && length (sequence) > 8)

Czech

Dictionary: Retrográdní morfematický slovník češtiny (1975)

Human Substitus
axióm axi-óm
bandask-a bandas-k-a
herald-ic-k-ý herald-i-ck-ý
krať-as krať-as
kvap-i-t kvapit
med-ov-ý med-ov-ý
na-hmat-a-t na-hmat-a-t
ne-dut-nou-t nedut-nout
po-č-ín-a-t po-čín-a-t
pře-krás-n-ě pře-krásn-ě
roz-louč-e-n-í roz-louč-en-í
říč-k-a říč-k-a
se-šláp-nu-t-ý sešláp-nut-ý
s-náš-e-n-l-iv-ě snáše-n-liv-ě
s-pj-a-t-ý spjat-ý
tur-ist-k-a tur-ist-k-a
unik-um u-niku-m
za-krát-k-o z-a-krátko
zá-lib-n-ě zálib-n-ě
žad-a-tel-k-a žadatel-k-a

Slovak

Dictionary: Morfematický slovník slovenčiny (1999)

Human Substitus
cenz-úr-a cenz-úr-a
do-modr-a« do-modra
furunkl-ov-ý furunk-lový
i-matr-ik-ul:ov-a:ť imatr-ikul-ovať
kmit-o-čet-∅ kmitoč-et
kvant-ov-ý kvant-o-v-ý
lombard-sk-ý lombard-s-k-ý
medzi-planet-ár:n-y medzi-planet-árn-y
piet-n-y piet-n-y
post-soci-al-ist-ic:k-ý post-sociali-stick-ý
pot-ent-át-∅ potent-át
pras-ac-in-a prasa-c-i-n-a
prav-ič-iar-∅ prav-ičiar
riž-sk-ý rižsk-ý
škrob-ár-k-a škrob-árka
t[adiaľ]« t-adia-ľ
[za]bud-n-u:t-ie za-bud-nu-t-i-e
za-tín-a:ť za-tín-a-ť
zn-ám-osť-∅ znám-os-ť
z-rum[en]-ie:ť zru-menieť

The most productive tokens found by Substitus

Here, productivity is defined as the number of word forms the token appears in, regardless their frequency. That’s why you will not find tokens like “but” here.

For each language, the tokens were extracted from a large web-corpus-based word list of one million most frequent word forms. The examples, shown in tooltips, are sometimes bad (especially for short tokens), but the tokens themselves should be fine.

Czech

Length #1 #2 #3 #4 #5
1 a i m e u
2 ov ne ch ho ou
3 ost pro pře roz při
4 teln www. před stav prav
5 proti spolu super jedno multi
6 instal obchod znamen středo inform
7 elektro kontrol program registr minutov
8 comment- několika kvalifik padesáti dokument
9 procentní prezident identifik administr miliardov
10 kilometrov zprostředk experiment spravedliv sedmdesáti

English

Length #1 #2 #3 #4 #5
1 s e n t a
2 er ed re al ly
3 ing ion man ist non
4 ness .com non- over able
5 ation based anti- inter ville
6 ' -style master school single
7 comment related million counter ability
8 american -looking oriented friendly specific
9 christian wikipedia sponsored conscious character
10 government controlled management washington california

German

Length #1 #2 #3 #4 #5
1 s e n t r
2 er en ge be an
3 ung ver ein end aus
4 isch lich chef über berg
5 spiel recht markt sport ation
6 system arbeit steuer schaft gruppe
7 konzern bereich politik projekt technik
8 geschäft programm internet sprecher zusammen
9 industrie präsident verfahren marketing transport
10 wirtschaft hersteller produktion sicherheit management

Hungarian

Length #1 #2 #3 #4 #5
1 k t e a i
2 ás és et at ra
3 nak meg nek ség ben
4 ként kkel nagy alap szak
5 össze ással vezet világ hitel
6 vissza ország csapat szabad jelent
7 verseny csoport kormány program politik
8 rendszer ingatlan fejleszt részvény tulajdon
9 miniszter szövetség szerződés gyógyszer fesztivál
10 szolgáltat élelmiszer társadalom információ tulajdonos

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Probabilistic tool for word segmentation to grammar-based units.

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